Towards a Framework for the Industrial Recommissioning of Residual Energy (IRRE): How to Systematically Evaluate and Reclaim Waste Energy in Manufacturing

Abstract

The extensive body of research dedicated to optimizing energy consumption and efficiency in the manufacturing sector demonstrates a significant and well-established legacy. Despite a peak of publications in this field over recent years, the subject of reusing residual energy is only infrequently discussed. Where authors target this topic, research is often exclusively directed towards specialized applications or industries. In this article, an initial attempt of approaching residual energy reclamation in industrial manufacturing in a structured and universal manner is made. By employing a systematic literature review and design science research, a universal tool chain for decomposing individual industrial manufacturing systems to successfully reclaim and reintegrate residual energy is developed. A comprehensive overview of technologies available for energy conversion in industrial scenarios and their corresponding efficiency ranges are presented in the form of a table, called the energy conversion overview (ECO) table. The main contribution poses a multistep sequential framework guiding through identifying, assessing, harnessing, reusing, and validating residual energy in manufacturing systems. As a universal tool, the Industrial Recommissioning of Residual Energy (IRRE) framework is empowering its adopters to systematically approach residual energy recovery in their individual context by a universal tool. The application of both tools is showcased in a case study from the large-aircraft carbon fiber manufacturing industry.

1. Introduction

As energy prices continue to rise, the significance of energy consumption in manufacturing becomes increasingly prominent. Consequently, there is a pressing need to optimize manufacturing processes and enhance their efficiency [1]. However, the interdependent nature of process-related requirements and the isolated certification procedures for production processes often render extensive changes to production systems economically unviable across many industries. Despite these challenges, reducing energy consumption necessitates a clear understanding of where energy losses occur within existing production processes and how these losses can be mitigated. Figure 1, as presented in [2], illustrates various types of energy waste. While some losses, such as those related to primary conversion and distribution (Figure 1, arrows 2 and 3), often lie beyond the control of those responsible for production systems, other losses can be addressed solely within the constraints of these systems themselves. The proposed framework in this article focuses on identifying these controllable losses and reducing them through the reclamation and reintegration of energy.

In this article, the production process is considered a closed system, where energy that is converted into a form no longer usable within the system is deemed a loss. It is crucial to emphasize that this energy, although not creating value in any process, is still physically present, as per the law of energy conservation, which states that energy is never lost or consumed but merely converted. However, in industrial practice, it is imperative to closely examine, analyze, and ultimately minimize all eight categories of energy losses illustrated in Figure 1. This article concentrates on repurposing previously unused residual energy from production processes to enhance overall efficiency.

In this context, efficiency is defined as the ratio of input or principal energy to value-adding energy, also referred to as active energy in Figure 1, expressed as a percentage, as shown in Equation (1):

$$\begin{array}{c}manufacturing process \\ energy efficiency\end{array}\left[\%\right]={\displaystyle \frac{value adding energy \left[kWh\right]}{principal energy \left[kWh\right]}}*100$$

(1)

Reusing available non-value-adding energy within the production system offers particularly large potential, since many technologies, tools, and methods for reusing this potential already exist. For example, waste heat recovery systems can capture and repurpose heat from industrial processes, while regenerative braking systems in electrical drives convert kinetic energy back into electricity. Additionally, air-to-air and air-to-liquid energy recovery systems can harness heat from exhaust gases to improve energy efficiency in manufacturing facilities as well. While already often discussed in the literature, the reuse of waste energy is currently not an established practice in industry. However, a trend can be observed that practitioners are becoming increasingly involved with this topic as well [3,4,5]. For this reason, the contribution at hand aims at guiding such efforts.

The width of the arrows in Figure 1 exemplarily illustrates the typical ratio of individual energy losses in production processes. Although losses due to lack of recovery (Figure 1, arrow 8) are relatively small compared to others, they play a significant role in the context of existing (brownfield) manufacturing facilities. In absolute terms, such non-reused energy often constitutes a substantial total amount of non-value-adding losses. For instance, a representative example described by [6] demonstrates an inefficiency of nearly 15% for energy conversion systems from electrical to mechanical due to thermal losses.

The approach of reintegrating residual energy is particularly interesting for improving brownfield manufacturing facilities, as already comparatively low investments and minor changes can often foster a substantial optimization of energy usage [7]. Since losses due to a lack of recovery (Figure 1, arrow 8) occur directly within the regarded systems, the reintegration of such energy has advantages in terms of overall efficiency by reducing total conversion, distribution, and storage losses due to the usual proximity of emission and reintegration points. In addition, analyses in the production of carbon fiber aircraft components have already shown great potential for the reuse of waste heat. Besides heat, there are also other potentials, such as mechanical and kinetic energy in industrial production. For this reason, it seems necessary to analyze production systems holistically for optimal energy coupling.

To date, the reuse of residual energy in industrial processes, especially in high-value sectors like the automotive and aerospace sectors, is an underexplored yet critical area in the literature. Despite its comparably small share among total energy losses, the cumulative effect of not recovering residual energy is deemed substantial, since industrial energy consumption alone exceeded 3.5 × 10⁷ GWh in 2021 [8]. It is particularly important in industries with high production rates, where already small improvements per part lead to significant total benefits [9,10]. The same is true for manufacturing of high-value goods, where the cost of losses is comparatively small and, therefore, improvements are potentially substantial from an energy perspective.

Current work on waste in industrial manufacturing predominantly emphasizes material reuse and recycling, as suggested by the waste hierarchy of [11,12]. This focus, while important for sustainable practices, does not account for the vast potential of energy reuse. The concept of zero-waste manufacturing [12,13] does not consider energy waste sufficiently. In instances where energy reuse is considered, the scope is usually limited to thermal energy [14]. Other forms of recoverable energy, such as mechanical and electrical energy, are scarcely addressed. There have been several studies and frameworks proposed for the collection and reintegration of residual energy in manufacturing processes. However, most of these approaches focus on specific industries or processes rather than providing a universal, structured approach. Applications being described by scholars, on the other hand, describe diverse scenarios ranging from data centers [15,16] to brewing technology [17] to printing machines [18]. All these publications on industrial applications share the focus on specific use cases and hardly employ any universal approaches. Already in 2012, ref. [5] proposed a “processes and systems approach” for general energy efficiency in manufacturing, presenting a well-acknowledged contribution to manufacturing’s general energy efficiency. However, the reuse of waste energy remained under-evaluated. Ref. [19] proposed a framework for waste heat recovery in the steel industry using a combination of technologies such as the organic Rankine cycle (ORC) and absorption heat pumps. While this study offers valuable insights, it is limited to the steel sector. Ref. [20] reviewed various heat pipe heat exchanger technologies for waste heat recovery in industrial processes. Although the review covers a wide range of applications, it does not provide a structured approach for energy reuse across different manufacturing sectors. Ref. [21] introduced a methodology for analyzing the potential of waste heat recovery in industrial processes using a pinch analysis. This approach helps identify opportunities for energy reuse but does not offer a comprehensive framework for implementation.

Ref. [22] presents the only universal approach for the collection and reintegration of residual energy in manufacturing processes to date. This framework consists of four main steps: (1) energy data collection and monitoring, (2) energy efficiency assessment, (3) waste energy recovery and reuse, and (4) continuous improvement and optimization. The authors emphasize the importance of a holistic approach to energy management in manufacturing, considering both energy efficiency improvements and waste energy recovery. They also highlight the need for real-time data collection and monitoring systems to enable accurate energy efficiency assessment and identification of waste energy recovery opportunities. While this framework provides a structured approach to energy efficiency analysis and waste energy reuse in manufacturing, it has some limitations. Firstly, the approach has a limited decomposition of energy flows in manufacturing processes. Secondly, the framework offers limited guidance for practical application in real-world manufacturing settings. However, only practical guidance ensures adoptability and applicability, leading to tangible improvements in energy performance.

In conclusion, while the concept of reusing waste energy in high-value and high-output manufacturing domains has gained occasional attention over the past years, there is a substantial lack of coverage for universal and systematic approaches in both practice and the literature. Most of the existing studies and frameworks are sector-specific or focus on particular technologies. To address this, a structured approach named the “Industrial Recommissioning of Residual Energy framework” (IRRE) has been developed and is introduced in this article. It serves as a tool for practitioners tasked to analyze and optimize production systems energy efficiency. As a key prerequisite, a literature review investigates different energy conversion mechanisms and their respective efficiencies. The findings are summarized in the “energy conversion overview” table (ECO). To demonstrate its feasibility, the framework is exemplarily applied in the large-aircraft manufacturing industry, which is showcased in a case study.

The structure of this article is as follows: Section 2 presents the methodology of the framework development using the design science research (DSR) approach. Furthermore, it presents the systematic literature review to identify energy conversion technologies and respective efficiency rates. Section 3 contains the findings from the literature review and introduces the ECO table, which is crucial for identifying and evaluating residual energy potentials within the IRRE framework. Section 4 presents a detailed description of the IRRE framework and its various phases. Section 5 illustrates the case study carried out to evaluate the IRRE framework. Section 6 discusses the practical and theoretical implications of the findings. The section gives a critical subsumption of the framework and its applicability. This article’s key findings are summarized. Section 7 contains the outlook, giving suggestions for future research in the field of residual energy reintegration.

2. Methods

2.1. Adapted PRISMA Approach for a Systematic Literature Review

The examination of the scientific literature plays a central role in understanding the current landscape of energy conversion techniques, particularly those with practical applications in industries. Focusing on industrially deployable technologies is crucial to ensure relevance and applicability in this contribution’s context. In pursuit of comprehensive insights while maintaining methodical coverage, this chapter adopts a systematic literature review approach. It is essential to note that the findings presented are reflective of the current state, bearing the possibility of evolving as new advancements emerge. Conducting a similar analysis at a later point should yield results that build upon and extend the findings presented here, showcasing the technological advancements in this field.

The systematic literature review was methodically based on an adapted PRISMA approach [23] and conducted to identify relevant industrial energy conversion mechanisms and their efficiency rates; publications until December 2023 were included. Three scientific databases, i.e., Web of Science (WoS), Scopus, and Google Scholar, were used to collect results from the search string “energy AND (conversion OR transformation OR transduction”, adjusted as needed for each individual search engine. As the resulting number of articles was too high, only the first 250 articles from WoS and Scopus and the first 500 articles from Google Scholar were considered, based on a sorting by relevance.

The inclusion of an additional 24 articles serves as a testament to the comprehensive nature of our research methodology. Employing an extended fuzzy search technique allowed for a more expansive exploration of individual energy conversion techniques, enriching the content for the development of the ECO table. This involved incorporating various periphrases relevant to each technique into the search engines, widening the scope of the search process [24]. Furthermore, to enhance the depth and relevance of our findings, consultations with industrial sustainability experts were instrumental in identifying the pertinent literature and refining our search parameters. These experts come from the industrial sectors of aircraft manufacturing, chemistry, steel, and waste and recycling management. They are environmentalists in an industrial context, sustainability project managers, manufacturing engineers for machines and plant design, and CEOs. Abstracts of articles found by this fuzzy approach were treated with higher priority and thus fed into the process after filter F3 as depicted in Figure 2.

The figure illustrates the entire literature selection process. After merging the search results from all the databases, duplicates were removed (Figure 2, F1). The remaining articles were filtered by title according to the filter description in Figure 2. Firstly, irrelevant terms, e.g., that focus on primary energy creation, were excluded by filter 2. Thus, the number of articles was eventually reduced to 576. These articles were filtered by title again (Figure 2, F3), this time including certain keywords (as depicted in Figure 2) to make sure the obtained articles are relevant in an industrial environment and not restricted to laboratory use cases only. After completing this filter, the publications found through the extended fuzzy search were added. Additions are mainly based on suggestions by the described experts. The resulting 122 articles’ abstracts were individually reviewed to identify relevant papers (F4). For the identification, we have taken into account the outcome of the interviews with designated experts from the fields described above. Ultimately, 45 articles were analyzed in detail. The results from this process are condensed to fill the ECO table presented in Section 3.

2.2. Applied Design Science Research for the Development of a Structured Framework for the Industrial Recommissioning of Residual Energy (IRRE)

The IRRE framework was built on the foundational principles of the design science research (DSR) methodology [26], a concept that originated in the field of information systems development. Over time, DSR has become a key method for predominant approach for systematically addressing complex conceptual problems. In design science, two main phases are crucial: the design cycle and the empirical cycle. These phases are iterative, each playing a unique role in the development and evaluation of solutions, or ‘artifacts’, tailored to particular problems and contexts [27]. The guiding research question which led to the development of the IRRE framework is “How can a structured process model be designed to reduce residual energy losses in various manufacturing settings, while also enhancing the profitability of applying organizations?” The IRRE framework is the final result of this process, developed through four iterations of the DSR design cycle. Creating the IRRE framework involved a three-step process within the design cycle: identifying the problem, designing a solution, and validating this solution [28]. The DSR term ‘treatment’ in this context refers to the interaction between the IRRE framework (and its predecessors) and the specific problem in different industrial manufacturing scenarios. The IRRE framework is designed to be universally applicable to various manufacturing processes within the boundaries of a defined production system. Each application of the framework in a manufacturing context requires addressing specific knowledge questions based on DSR principles. The IRRE framework is a dynamic tool for identifying, reclaiming, and reintegrating residual energy in manufacturing where such energy is underutilized. Within the DSR framework, the validation process includes predicting how these solutions will perform in specific situations. This process of forecasting and reapplying optimization potentials takes place in the ‘Assess’ and ‘Harness’ stages of the IRRE framework, which will be described in the following Section 4.

3. The Energy Conversion Overview (ECO) Table

For the estimation and classification of suitable energy conversions within the framework, a table was created based on an extensive literature search, as described in Section 2. The data from the previously described literature review are aggregated here to be readily accessible for adopters of the IRRE framework, since it constitutes its most important tool for energy system evaluation. This table, which is called the “energy conversion overview” (ECO) table (Table 1), depicts common conversion technologies deemed industrially exploitable, by findings from the review.

To be able to evaluate recognized energy reuse potential, the efficiencies of the individual forms of physical conversion are also summarized. For conversion mechanisms that convert heat, the coefficient of performance (COP) and the energy efficiency ratio (EER) are used, both of which represent the ratio of the energy input to the energy output [29,30]. For a harmonized view, the general conversion efficiency is chosen as the comparative value of the individual mechanisms. Calculations from [2] are extended, and the conversion efficiency (Equation (2)) is defined as the potentially value-adding energy output divided by the energy input reclaimed from the residual energy source.

Table 1. Energy conversion overview (ECO) table.

From/to ↱	Chemical (C)	Thermal (T)	Mechanical (M)	Electrical (E)
Chemical (C)	Not applicable	Combustion reaction	Internal combustion engine	Fuel cell
Efficiency:		51% to 99% 3	11% to 37% 8	70% to 100% 11
Thermal (T)	Endothermic process	Heat exchanger	Not applicable	Thermoelectric cooling
Efficiency:	19% to 90% 1	15% up to 95% 4		25% to 90% 12
Mechanical (M)	Not applicable	Friction	Gears	Generator
Efficiency:		35% to 45% 5	81% to 99% 9	60% to 92% 13
Electrical (E)	Electrolysis	Resistance heating	Electric motor	Electric transformer
Efficiency:	60% to 95% 2	98.5% to 100% 6	70% to 96% 10	96% to 99.75% 14
Electro- magnetic (EM)	Not applicable	Solar absorption	Not applicable	Photovoltaic cells
Efficiency:		50% to 96% 7		20% to 49% 15

Efficiencies according to ¹ T/C [31]; ² E/C [32,33,34]; ³ C/T [35]; ⁴ T/T [36,37,38]; ⁵ M/T [39]; ⁶ E/T [40,41]; ⁷ EM/T [42,43]; ⁸ C/M [44]; ⁹ M/M [45]; ¹⁰ E/M [46]; ¹¹ C/E [47,48,49]; ¹² T/E [50,51]; ¹³ M/E [52,53]; ¹⁴ E/E [54]; ¹⁵ EM/E [55,56,57,58].

Table 1. Energy conversion overview (ECO) table.

From/to ↱	Chemical (C)	Thermal (T)	Mechanical (M)	Electrical (E)
Chemical (C)	Not applicable	Combustion reaction	Internal combustion engine	Fuel cell
Efficiency:		51% to 99% 3	11% to 37% 8	70% to 100% 11
Thermal (T)	Endothermic process	Heat exchanger	Not applicable	Thermoelectric cooling
Efficiency:	19% to 90% 1	15% up to 95% 4		25% to 90% 12
Mechanical (M)	Not applicable	Friction	Gears	Generator
Efficiency:		35% to 45% 5	81% to 99% 9	60% to 92% 13
Electrical (E)	Electrolysis	Resistance heating	Electric motor	Electric transformer
Efficiency:	60% to 95% 2	98.5% to 100% 6	70% to 96% 10	96% to 99.75% 14
Electro- magnetic (EM)	Not applicable	Solar absorption	Not applicable	Photovoltaic cells
Efficiency:		50% to 96% 7		20% to 49% 15

Efficiencies according to ¹ T/C [31]; ² E/C [32,33,34]; ³ C/T [35]; ⁴ T/T [36,37,38]; ⁵ M/T [39]; ⁶ E/T [40,41]; ⁷ EM/T [42,43]; ⁸ C/M [44]; ⁹ M/M [45]; ¹⁰ E/M [46]; ¹¹ C/E [47,48,49]; ¹² T/E [50,51]; ¹³ M/E [52,53]; ¹⁴ E/E [54]; ¹⁵ EM/E [55,56,57,58].

$$conversion efficiency={\displaystyle \frac{value adding energy output}{reclaimed energy input}}$$

(2)

An understanding of the available conversion mechanisms makes it possible to better map the possible points of energy reclamation and reintegration during the framework’s corresponding phases (Section 4). This is particularly relevant in cases where it might be more efficient to change the physical form of energy before its reintegration in a manufacturing process. In the context of this table, the physical forms of nuclear and gravitational energy are not considered, as they are believed to have minor relevance to civil industrial application today. The conversion of existing forms of energy into electromagnetic energy is also not included, as this form of energy plays a subordinate role in industry as well, and related technologies do not represent any advantages for conversion, according to the findings from the literature review (Section 2.1). Some of the transmission mechanisms work bidirectionally. For the sake of clarity, these mechanisms have not been included twice. In the ECO table, all mechanisms display the energy conversion they perform from column (left) to row (above). When selecting mechanisms and efficiencies, the focus was laid on systems, which are beyond laboratory development and can readily be used industrially. This means that technologies not listed in this table still may already be known and proven feasible but are not ready for adoption in industrial application. The presentation of efficiencies is based on publications depicting industrial applications and does not include theoretically achievable conversion efficiencies. The ECO table is therefore just a snapshot of technologies and their development status at the time of writing. Findings presented here are likely to change due to continuous development. Furthermore, it is to be noted that, in many cases, efficiencies of individual mechanisms are dependent on the specific input characteristics or composition. The relevant properties are, e.g., the energy density, availability patterns (time dependence), interdependence of adjacent manufacturing processes, and downstream system requirements. This must be considered, and an appropriate investigation must be made when selecting adequate technology for any specific use case.

Financial aspects can play an important role when choosing technology, as in particular, the highest efficient systems are mostly more expensive [59,60,61]. For this reason, the latter-described IRRE framework (Section 4) emphasizes a holistic economic evaluation to accompany efficiency and feasibility considerations. For those reasons, the table only provides an overview of existing mechanisms and published efficiency values that are validated or proven in an industrial environment today. The ECO table presents a range of efficiencies for various energy conversion mechanisms, influenced by several factors. Firstly, environmental factors specific to global locations can impact efficiency, although these are not considered in the current analysis. Secondly, the efficiency of these mechanisms is contingent upon the industrial application scenario and associated environmental conditions. Furthermore, different technologies, each with varying levels of technological readiness, can contribute to the same energy conversion mechanism, resulting in a broad spectrum of efficiencies. It is crucial to recognize that the ECO table serves as an introductory tool for the preliminary evaluation of potential energy conversion mechanisms and should be regarded as a general guideline.

4. The Framework for the Industrial Recommissioning of Residual Energy (IRRE)

To comprehensively leverage the insights gained from the earlier literature analysis in the context of industrial manufacturing, [62] strongly recommends the adoption of a structured procedural model. The framework for the Industrial Recommissioning of Residual Energy (IRRE) represents such an approach, focusing on the enhancement of manufacturing systems through the lens of energy efficiency and the reclamation of residual energy. The framework’s five-step approach systematically breaks down the entire process of recovering previously untapped residual energy into clear and manageable phases. These phases, namely, “Identify”, “Assess”, “Harness”, “Reuse”, and “Validate”, are sequentially organized to guide the execution of a residual energy reclamation initiative. Each key phase is further delineated into detailed sub-activities as needed. Figure 3 offers a visual guide, depicting the content-related and chronological interactions among all the activities within the framework. Also, it gives a summary on all the necessary inputs and outputs from each of the IRRE framework’s phases being described in the following sections.

The schematic representation offers a concise overview of how the phases build on one another over time. Each discrete activity within the framework is specifically oriented towards the recovery of waste energy categorized under the designation of number 8, denoted as “lack of recovery” as outlined in [2] within the taxonomy specified in Figure 1.

Prior to initiating work within the framework, it is imperative for its users to delineate the system boundaries for the targeted system under observation. The establishment of system boundaries is a foundational step [63]. Given that the framework is explicitly tailored to reclaim residual energy within serial production, the encompassing scope of “production” within the overarching business context is the pertinent boundary to be selected. Entities operating in managerial or accounting capacities lie beyond the scope delineated for consideration within the framework context. However, certain ancillary activities intricately linked to production and providing direct support at the hardware and material levels warrant discussion within the framework’s purview. These encompass, among others, maintenance related to tooling, intra- and inter-logistics or support systems involving mediums such as heat, air, or hydraulics. Decisions regarding the inclusion of these activities within the framework’s contemplation are to be deliberated upon by the framework’s users. The decision on incorporating support functions should focus on their direct linkages to energy flows within production. Spatial proximity and interconnectedness with energy usage are key [64].

For example, while the provision of jigs and tools can be crucial for production, this function typically lacks direct energy interconnection with production machinery. Hence, including such functions within the system boundaries when using the framework might not be advisable if they have limited impact on energy supply, usage, and consequently reclamation potential within production processes. On the contrary, support mediums, like compressed air, often serve as prerequisites for value-adding activities. Often, they are strategically located in proximity to minimize piping length. The energy usage of these support mediums is induced by production activities. As a result, including these support activities within the system boundaries can be necessary. Once the system boundaries for the application of the IRRE framework are established, along with a shared comprehension of the processes, steps, equipment, and machinery encompassed within the investigation scope, the practical implementation of the framework commences with its initial phase, “Identify”.

4.1. Identify

The initial step for the Industrial Recommissioning of Residual Energy is the identification of residual energy and its release points. This step establishes the baseline for potential reclamation. It is essential to define the type of energy (Table 1) being released from value-adding production activities, along with its overall quantity, flow rate, and characteristics (continuous, intermittent, or discrete). These details need clarification before selecting reclamation points, technologies, storage, transportation, and reuse methods for such energy. The identification process can be accomplished in two different procedures: Progressive and regressive identification of potential residual energy. Both procedures encompass the expansive scope established by the predefined production system boundaries. They utilize distinct strategies to transition from a broad perspective towards a more intricate and detailed examination. The progressive strategy delves into discerning energy consumers and their corresponding energy pathways, while the regressive strategy focuses on pinpointing energy surplus points at the level of tools and machinery within the system. The different approaches are visually delineated in Figure 4.

Progressive Identification, depending on the level of knowledge about machinery and equipment employed, is typically the more precise method of identifying residual energy. The approach initially defines the principal energy inputs based on the physical forms of energy (Table 1) utilized within the given context. This includes categorizing energy sources such as electricity, combustible fuels, or even forms of natural or artificial radiation. It is essential that these inputs are measurable and thereby quantifiable. Following the definition of these principal energy inputs, the subsequent step involves defining the pathways that dictate the direction and supply of energy. This step can already reveal initial instances of non-value-adding energy loss, considering that many energy transmissions operate at efficiencies below 100%. The precise segmentation of distinct levels of decomposition is context-dependent. However, it commonly involves categorization into distinct tiers, including main transmission, switching, equipment, internal relay, machinery, control systems, and energy conversion devices, manipulators, or tools (Figure 4). Consequently, the route and distribution of all principal inputs within the established system boundaries are decomposed, fostering a detailed comprehension of each individual energy consumer or transformer and its specific energy requirements.

Regressive identification, unlike the progressive approach, starts by examining the variety of the system’s energy dispatches. It employs a broader heuristic approach. Beginning from the system’s output, the regressive method retraces steps backward through the production system. It identifies machinery, equipment, and their energy supply systems, the transmission pathways (Figure 4). The goal is to define areas where energy dissipates without further contributing value to the process. This method offers an alternative view, exploring the system backward from its residual energy output to uncover inefficiencies or non-value-adding energy losses, providing deeper insights into energy behavior within the production system. Regressive identification is an alternative to execute the “Identify” phase, where project resources or knowledge about machinery and equipment internals is scarce or key imitation points are already well known.

In both approaches, principal energy which does not inherently become part of the final manufactured good post-production can be classified as either value-adding or non-value-adding. However, this energy consistently emerges as residual energy, presenting itself as potentially available for reclamation. The progressive method, being deterministic, provides more detailed results but usually requires more work due to its comprehensive nature. On the other hand, the regressive method, although heuristic and less precise, operates faster and may suffice for specific contexts or scenarios.

4.2. Assess

Within the IRRE framework’s “Assess” phase, an examination of residual energy identified during the “Identify” phase defines the specific attributes of this energy while focusing on precise quantification and understanding its physical form (e.g., electrical or thermal energy). This phase delves into evaluating the dynamics of energy flow, determining whether it is continuous, intermittent, or a hybrid, non-consistent, swelling pattern. Additionally, it assesses the extent of the manufacturing process’s reliance on energy, revealing its degree of indispensability. This analysis constructs a profile of the production systems’ residual energy matrix, serving as the foundation for strategic decisions and optimal strategies for reclaiming and effectively utilizing this energy within the manufacturing system.

Therefore, the “Assess” phase is divided into two critical sub-phases: “Quantify” and “Reclaim.” The “Quantify” sub-phase involves focusing on precise measurement and documentation of residual energy volume, spatial dispersion, flow patterns, and temporal occurrences within the manufacturing domain. Subsequently, the “Reclaim” phase contains an evaluation, aiming to determine the technological feasibility of reclaiming identified residual energy sources. This phase anchors onto technological assessments, seeking practical viability and methodologies to ensure the ability of the reclaimed residual energy to reintegrate into the manufacturing ecosystem during a later phase. Overall, this assessment serves as a bridge between identifying potential energy sources and implementing reclamation strategies.

“Quantify”, as the “Assess” phase’s first sub-phase, describes a step-by-step exploration, navigating through tasks pivotal in understanding the nature and dynamics of residual energy. Energy Form Identification: The initial task within the “Quantify” phase involves deciphering the inherent forms of residual energy. It categorizes and identifies the physical manifestations of energy as per Table 1, whether electrical, thermal, or alternative forms. Understanding these energy forms serves as a foundational step in comprehending their properties and potential avenues for reclamation. Following the identification of energy forms, the next task delves into a quantitative analysis. It involves precise measurement and quantification of the residual energy present within the manufacturing domain. The exact amount of residual energy is determined, facilitating an understanding of its quantitative impact on the system. Understanding the temporal occurrences of residual energy over time constitutes the subsequent task through examining the frequency and patterns of energy occurrences. Understanding the flow patterns, whether continuous or intermittent, aids in identifying potential areas of energy accumulation or dissipation, crucial for reclamation strategies. This sub-phase’s final task is a spatial analysis, assessing the spatial dispersion patterns of residual energy within the manufacturing domain. This examination sheds light on the distribution and concentration of energy across different areas. Understanding the spatial nuances helps pinpoint specific locations where residual energy accumulates or remains underutilized. During the “Quantify” sub-phase, caution must be exercised in data interpretation due to the intricate nature of energy dynamics. Clear, unbiased, and structured documentation holds importance as it forms the foundation for subsequent phases within the framework. Thorough and transparent documentation ensures that the insights, interpretations, and conclusions drawn from the quantitative analysis of residual energy characteristics remain accessible and comprehensible to all stakeholders.

“Reclaim”, the subsequent sub-phase within the IRRE framework, aims to evaluate the technological feasibility of reclaiming identified residual energy sources and ensuring their practical viability for reintegrating into the manufacturing ecosystem. The overarching goal is to devise a theoretical blueprint detailing which residual energy to harvest and its intended utilization. This approach is imperative, aligning the earlier-identified residual energy potential with the energy demand of other manufacturing processes currently reliant on principal energy sources. To achieve this alignment, technologies for converting, storing, and transferring energy, as specified in Table 1, can be employed. One promising technology which aligns with the goals of the IRRE framework is, for example, the Maisotsenko power cycle (M-cycle). The M-cycle, as described by [38], is a thermodynamic process that utilizes the latent heat of water evaporation to enhance energy conversion efficiency. Originally applied in air-conditioning systems, the M-cycle has demonstrated significant potential in power generation and heat recovery applications due to its ability to achieve high thermal efficiency and reduce pollutant emissions.

The reclaim phase mandates an initial assessment encompassing potential residual energy supply, plausible energy consumers, and technological feasibility, including efficiency evaluations of storage, transmission, and conversion systems (Table 1). The ultimate criterion involves ensuring that the total available energy supply either matches or surpasses the total demand per energy form, factored by the efficiencies of storage, transmission, and conversion systems (see Equations (2)–(5)). The calculation of the overall efficiency involves ensuring that the total supply of residual energy equals or exceeds the total demand per energy form, considering the efficiencies of storage, transmission, and conversion systems as multipliers, to ascertain a sustainable surplus or an equilibrium in the manufacturing energy ecosystem (Equations (3) and (4)). This assessment forms the bedrock for a successful reclamation of residual energy within the specified manufacturing system. Upon completing the “Reclaim” sub-phase, framework users should have gathered comprehensive insights into the technological feasibility, matching supply and demand efficiencies, and a strategic blueprint for reclaiming and effectively integrating identified residual energy sources into the manufacturing ecosystem.

4.3. Harness

The “Harness” phase within the IRRE framework is dedicated to detailed planning of the technical aspects associated with reclaiming residual energy. This phase is the focal point of the framework, concentrating all energy-related planning activities within its ambit. The preceding phases lay the necessary groundwork for this phase again. The “Harness” phase is subdivided into four interconnected sub-phases: “Collect”, “Convert”, “Store” and “Recommission”. While the first and last sub-phases are mandatory, the intermediate phases, “Convert” and “Store”, are presented as optional components. These sub-phases are aligned with the direction of energy flow, tracing from the point of residual energy emission to its reintegration. However, the order of executing these sub-phases is not rigidly defined, depending on contextual specifics. The sub-phases “Convert” and “Store” are not inherently sequential, allowing flexibility. For instance, collected energy might be stored first and converted subsequently if the technology employed indicates higher efficiency or lower costs. This adaptability ensures a pragmatic approach based on the dynamics of energy utilization and technological feasibility. Storing energy becomes essential when temporal decoupling is required due to the mismatch between the emission of residual energy and the demand for reclaimed energy. Conversion processes are imperative when the physical form of residual energy differs from the required physical form of energy on the demand side.

Following the identification of all energy-consuming processes relevant to potential energy reintegration during this phase’s sub-phases, the subsequent step involves evaluating the overall efficiency and associated costs. This evaluation necessitates assessing the efficacy and financial implications tied to each potential reintegration point. Ultimately, a list of identified collection and reuse points in the production system at hand must undergo sorting to prioritize those that exhibit the optimal alignment between energy supply and demand while considering associated costs. The reduction in principal energy required within the manufacturing domain directly impacts the payable energy amount, hence emphasizing that all evaluations are inherently grounded in monetary assessments. This monetary evaluation serves as the underlying basis for decision making within this phase. It is carried out by evaluating each potential collection and reuse point combination’s present value [65]:

$$PV={\displaystyle \sum }_{t=0}^{t_{max}}{\displaystyle \frac{{{\displaystyle \int }}_t^{t+1}\Phi \left(t\right)\cdot {{\displaystyle \prod }}_{i=1}^n{\eta }_{tran{s}_{it}}\cdot {{\displaystyle \prod }}_{j=1}^m{\eta }_{stor{e}_{jt}}\cdot {{\displaystyle \prod }}_{k=1}^o{\eta }_{conver{t}_{kt}}dt\cdot p_t-C_t}{{\left(\sqrt[q]{r_{annual}+1}\right)}^t}}$$

(3)

The subsequent

Table 2. Variables used in evaluating energy reintegration and their respective units.

Variable	Definition	Unit
PV	Present value	[€]
t	Period $\left(Period duration \left[s\right]={\displaystyle \frac{senconds per year}{q}}\right)$	unitless
Φ(t)	Residual energy emission power per period	[W]
ηtrans/store/convert	Efficiency of transmission, storage, and conversion system	[%]
i, j, k	Individual transmission, storage, and conversion system	unitless
n, m, o	Number of transmission, storage, and conversion systems	unitless
pt	Principal energy price per unit per period	[€/Ws]
Ct	Recurring and non-recurring cost of energyreclamation implementation and operation per period	[€]
q	Number of periods per year	unitless
rannual	Annual internal interest rate	[%]

details the key variables employed in evaluating energy reintegration and conducting financial assessments, particularly in calculating the present value (PV) associated with the investment or project.

The “present value” (PV) (Equation (3)) is a standardized method for assessing the current worth of future cash flows, considering discounting based on internal interest rates [66]. By assessing the costs and benefits over time, PV helps determine the feasibility and profitability of harnessing and reintegrating residual energy. This calculation allows adopters of the framework to compare the current worth of anticipated gains against the initial investment and recurring costs. Ultimately, it aids in decision making regarding the adoption and implementation of specific energy reclamation strategies by providing a comprehensive financial perspective within the framework’s “Harness” phase. For calculating a reclamation source’s present value, variable t delineates the duration of each assessment interval denoted as a period, essential for understanding energy fluctuations over time. Φ(t) signifies the emitted residual energy, influencing decisions on energy collection and reclamation strategies. The efficiencies η_{trans/store/convert} reflect the effectiveness of systems involved in transmission, storage, and energy conversion. Variables p_t and C_t are instrumental in cost analysis, encompassing the price of substituted principal energy and operational expenses linked to energy reclamation efforts. The parameters q and r_annual offer insights into the frequency of assessment periods and the annual internal interest rate, respectively. Their embodiment is to be individually decided on by the framework’s adopters.

“Collect”, as the first sub-phase, is where the energy form intended for reclamation, along with its flow pattern, quantity, and emission point, is already known from the “Assess” phase. Commencing planning for the energy’s reintegration initiates at this stage to ensure comprehensive coverage. Within the “Collect” sub-phase, the primary objective is the identification of potential points of residual energy emission and points for its reuse. Leveraging the insights obtained during the “Identify” phase becomes integral for recognizing processes within the system that require energy, possessing similar physical properties and patterns of occurrence. Adopters must focus on identifying every emission point within the production system where residual energy is released. Furthermore, they must concurrently contemplate and plan for potential reclamation technologies, referring to the technology matrix outlined in Section 3. The outcome of this phase should manifest as a comprehensive list of energy sources, detailing their respective energy forms, quantified emission amounts, and the associated technologies primed for deployment in collecting this residual energy.

“Recommission”, the second essential sub-phase within the harness phase, focuses on the crucial task of identifying reintegration points for previously reclaimed residual energy. This phase aims to utilize prior knowledge to identify the processes most compatible with reclaimed energy. It involves comprehensive technological planning for reintroducing the reclaimed energy. Prior to deciding on the technology to facilitate this reintroduction, it is imperative to define all potential reintegration points within the predetermined production system context. This entails evaluating all energy-consuming processes, assessing their overall energy demand, demand patterns, and the physical form of energy they require. Once the potential points for energy reintegration are identified, along with the specific physical energy required for each, the alignment between reclaimable energy potentials and energy demands becomes feasible. As mentioned in the introduction of this chapter, the optimal match occurs where minimal losses are anticipated during energy transmission, storage, and conversion processes. This alignment ensures the most suitable match between the flow and occurrence patterns of the supplied and demanded energy. Concluding this sub-phase is the list of potential reintegration points, which augments the list of reclamation points from the “Collect” sub-phase. A matrix containing these points needs to be established, followed by an evaluation of each field within the matrix, assessing every reclamation point combined with every reintegration point. For combinations deemed both technologically feasible and promising for further evaluation, adopters are required to outline energy flow pathways and suggest employable technologies, based on Table 1.

“Convert”, as one of the two optional sub-phases within the IRRE framework’s “Harness” phase, is often indispensable in many real-world applications. A conversion system may be essential despite no actual change in the physical form of energy being needed. For instance, manipulating electrical voltage levels using transformers or accumulating heat through heat pumps is indeed not changing the physical form of energy, but it still requires some technological approach to be accomplished. Despite maintaining the energy’s physical form (such as electrical or thermal), these instances necessitate some form of conversion, often leading to inherent losses due to employed technologies. The objective of this sub-phase is to establish compatibility between the identified reclaimed energy flow, as determined in the “collect” phase, and the energy requirements defined for reintegration, as planned in the “recommission” phase. This is achieved through the selection of suitable technology by the adopters, utilizing the technology matrix provided in Section 3. The aim is to align the reclaimed energy flow with the reintegration requirements by choosing the most fitting technological solutions from the matrix.

“Store”, as the second of the two optional sub-phases, becomes necessary when the temporal energy flow patterns between the energy source (where residual energy is reclaimed) and the energy sink (where residual energy is reintegrated) do not align. This need for storage is initially independent of the physical form of energy at both the reclamation and reintegration points. Adopters are tasked with assessing the storage technology based on the specific physical form of energy at the reclamation point and the required form at the reintegration point. Storing energy in a physical form that differs from that present at the source and is unnecessary at the sink is generally unfavorable. It usually leads to an additional energy conversion step, resulting in further losses. Determining the storage capacity relies heavily on the temporal flow patterns and the contextual intricacies of the production system at hand. Specific guidance regarding quantifying storage needs is outlined in the following. The equations presented in the following are pivotal in gauging the fit between the energy generated and utilized within a system. They enable an assessment of the necessity for storage solutions, detailing the required capacity and specifications for storage systems if deemed essential. They serve as quantitative tools to streamline decision-making processes regarding energy reclamation, reintegration, and storage within the defined production system.

Equation (4) serves to delineate the compatibility between the energy source (residual energy collection point) and the energy sink (reintegration point) where this energy is utilized anew. It encompasses the efficiencies inherent in transmission and conversion systems utilized for energy transfer across various physical forms. The condition, if met consistently across all periods t, indicates the obsolescence of energy storage.

$$\begin{gathered} {{\displaystyle \int }}_t^{t+1}\left(\Phi \left(t\right)\cdot {\displaystyle \prod }_{i=1}^n{\eta }_{tran{s}_{it}}\cdot {\displaystyle \prod }_{k=1}^o{\eta }_{conver{t}_{it}}\right)dt \ge {{\displaystyle \int }}_t^{t+1}\Psi \left(t\right)dt \\ \forall t \in \left[1,t_{max}\right], \forall i \in \mathrm{I}, \forall k \in \mathrm{K}; s.t. \left|I\right|=n,\left|K\right|=o \end{gathered}$$

(4)

By comparing the total amount of energy reclaimed, by determining the integral over the source point’s emission and its affiliated efficiencies, to the integral over the energy flow at the reintegration point, Equation (4) indicates the matching of two distinct energy sources and sinks per period. Once the residual energy Φ(t) is available, deducted of all inevitable losses η, exceeding or equal to the energy demand Ψ(t) at the point of reintegration for every period t ∈ [1, t_max], no storage system will be needed. Equation (4) expects no additional principal energy to be added to complement reintegrated energy.

Once the residual energy Φ(t), deducted of all inevitable losses η, does not at least equal the energy demand Ψ(t) for one or more periods t of all periods under consideration, an energy storage system might be added to the energy pathway between the source and sink. While this increases the likeliness of matching the source and sink despite deviating energy flow patterns, additional storage increases initial invest, recurring cost and energy losses. By employing Equation (5), adopters can determine if the source and sink match from the perspective of the quantity of energy over all periods under consideration. This is performed by determining and comparing the integrals for both the energy flow at the source point Φ(t) including losses η and the required energy flow at the sink Ψ(t) over all periods t ∈ [1, t_max].

$$\begin{gathered} {{\displaystyle \int }}_1^{{\mathrm{t}}_{\max }}\Phi \left(\mathrm{t}\right)\cdot {\displaystyle \prod }_{i=1}^n{\eta }_{tran{s}_{it}}\cdot {\displaystyle \prod }_{j=1}^m{\eta }_{stor{e}_{jt}}\cdot {\displaystyle \prod }_{k=1}^o{\eta }_{conver{t}_{kt}}dt \ge {{\displaystyle \int }}_1^{t_{max}}\Psi \left(t\right)dt \\ \forall t\in \left[1,t_{max}\right], \forall i\in \mathrm{I},\forall j\in \mathrm{J},\forall k\in \mathrm{K}; s.t. \left|I\right|=n,\left|J\right|=m,\left|K\right|=o \end{gathered}$$

(5)

If a match between the energy source and sink, despite considering storage, is not achievable or if the costs involved are excessively high, supplementing with additional principal energy might become necessary. However, this approach tends to diminish the overall efficiency of the system when compared to driving specific processes solely by reclaimed residual energy. In cases where storage is utilized to accomplish manufacturing processes being supplied by reclaimed energy only, it is crucial to determine the minimum storage capacity required to secure steady supply. Using Equation (6), adopters can ensure supply by calculating the highest deviation between the sink demand and source supply over the course of all planning periods t. The total amount of energy supplied, Φ(t), and deducted, Ψ(t), from the storage system is calculated by fixing the integrals’ lower bounds to t = 1 and calculating the amount of energy contained in the storage system for every upper bound (t_end) ranging from t = 1 to t = t_max. By doing so, adopters gain insight on the highest overall deviation between the energy obtained from a reclamation source and an energy-demanding sink over the course of all planning periods. Efficiencies of all systems involved according to Table 1 are considered by their respective factors η.

$$\begin{gathered} \underset{1\le t_{end}\le t_{\max }}{\max }\left({{\displaystyle \int }}_1^{t_{end}}\Psi \left(t\right)dt-{{\displaystyle \int }}_1^{t_{end}}\Phi \left(t\right)\cdot {\displaystyle \prod }_{i=1}^n{\eta }_{tran{s}_{it}}\cdot {\displaystyle \prod }_{j=1}^m{\eta }_{stor{e}_{jt}}\cdot {\displaystyle \prod }_{k=1}^o{\eta }_{conver{t}_{kt}}dt\right) \\ \forall i\in \mathrm{I},\forall j\in \mathrm{J},\forall k\in \mathrm{K};s.t. \left|I\right|=n,\left|J\right|=m,\left|K\right|=o \end{gathered}$$

(6)

All equations presented above assume a holistic substitution of a certain energy demand by reclaimed energy. If only a partial substitution of principal energy by reclaimed energy reintegration is accomplished, Equations (5) and (6) must be adapted to determine the lowest cost by balancing the storage dimension and principal energy required.

4.4. Reuse

During the “Reuse” phase, the theoretical groundwork established in the preceding “harness” phase is consolidated. This phase involves an assessment of the numerous permutations of points designated for energy reclamation and reintegration. Adopters are tasked with selecting the combinations of the energy source and sink that yield the highest present value (PV) while remaining technically viable. Upon compiling a list of potential combinations, subsequent planning must focus on actualizing each selected combination. In this context, adopters are required to reassess the pre-designed energy pathway, following a procedure akin to the previously described progressive identification method (Section 4.1). The process begins with the selection of equipment to gather the residual energy that has thus far been emitted into the production system’s vicinity. Next, the transmission system must be planned for realization. Following this, the planning involves setting up the transmission system for implementation. Subsequently, the design extends to include conversion and storage systems, contingent upon their necessity derived from the match between the energy sink and source, as previously described. Lastly, the plan encompasses reintegration strategies, focusing on substituting principal energy for the process at the point of reintegration.

In documenting the outcomes of this phase, adopters ensure comprehensibility of the pathway re-evaluation, system planning, and reintegration strategies. An energy pathway re-evaluation report should detail the reassessment and selection of equipment for energy collection. System planning documentation outlines the transmission, conversion, and storage system plans derived. Finally, a reintegration strategy overview document can encapsulate the strategies devised to substitute principal energy at the reintegration point, reflecting the nuanced decisions made during this phase of the framework. Documentation stands as the cornerstone for sustainable decision making and further progress within the energy reclamation process. The documents described here do not originate from an explicit template but should be created by each user of the framework at their own discretion and in coordination with the documentation requirements of the entire project team and the superordinate structure. Documentation is not about satisfying a system but about preparing and storing adopters’ own results in a way that is sustainable and understandable for others.

4.5. Validate

This last phase of the IRRE framework involves reassessing all critical aspects of prior phases after commissioning. First, it requires an examination of performance metrics established during the prior phases. This evaluation involves measuring the effectiveness of the energy reclamation system in meeting predetermined performance criteria. Simultaneously, an efficiency analysis is conducted to assess how efficiently the reclaimed energy system operates compared to principal energy, aiming to quantify the gains achieved through reclamation efforts. A crucial component of validation is the thorough evaluation of the technologies employed within the system. This technology assessment includes reviewing the reliability, functionality, and suitability of the chosen technologies for the intended purpose. Economic viability plays a pivotal role in the validation process. It involves a review of the cost–benefit analysis, comparing the actual economic benefits realized from the reclamation process against initial estimations. This assessment also considers the return on investment and overall financial feasibility. Additionally, the environmental impact assessment is vital for examining the system’s effects on the environment. This includes analyzing emissions, resource conservation, and the overall ecological footprint, ensuring the reclamation process aligns with sustainable practices.

The validation phase also addresses system reliability by subjecting the reclaimed energy system to various scenarios and conditions to test its resilience, dependability, and robustness. A sensitivity analysis for variations in production schedules might support the robustness estimation [67]. Operational testing is conducted in real-world scenarios to validate the system’s functionality and efficiency under practical conditions. Data monitoring and analysis are fundamental throughout the validation phase. Continuous data collection and analysis are critical to ensure that the system operates as intended and to identify any anomalies or inefficiencies that require attention.

5. Application of the IRRE Framework in Large-Aircraft Carbon Fiber Manufacturing

The case study highlights the use of the Industrial Recommissioning of Residual Energy (IRRE) framework in the production of carbon fiber aircraft parts at a major European aircraft manufacturer, as “an intensive study of a single unit with an aim to generalize across a larger set of units” [68]. This study aims to show how the IRRE framework can be applied in a high-value industry like aircraft manufacturing, where energy efficiency often receives less focus due to the complexity of production systems. By implementing the IRRE framework, this study demonstrates its potential, especially in industries with lower output. The positive results suggest that the framework could be adapted to other industries, proving its versatility.

Aircraft manufacturing processes are typically certified and based on established systems, making changes difficult and costly. This underscores the challenge and importance of integrating energy-saving projects in such complex and financially constrained environments. This study focuses on the resin transfer molding (RTM) process, which involves heating and cooling cycles during preparation, curing, and part removal stages. This process is the most energy-intensive phase in producing carbon fiber components, making it an ideal area for exploring energy recovery strategies and improving overall energy efficiency [69]. The RTM process is sequential and relatively simple, allowing for detailed observation and analysis of energy use and potential recovery opportunities at each step. This characteristic makes it easier to identify and implement energy-saving measures.

In this case study, the manufacturing target is 50 parts per month, a common rate in large-aircraft manufacturing. The RTM process involves several key heating steps, as shown in Figure 5. The sequence begins with preheating the resin from room temperature to 50 °C, followed by heating the tooling to 140 °C. Next, resin infusion occurs under high pressure at 50 °C to 80 °C. The final phase involves curing the part in a closed mold under pressure at 140 °C to 180 °C.

During an RTM cycle, various machines consume significant energy. The resin heating system is crucial for preparing the resin for infusion and curing. Mold heating devices are essential for preheating the mold and during curing cycles. The press machinery ensures proper mold closure during resin injection and opening for component removal. The resin pump provides the necessary pressure for resin infusion, and a cooling system regulates the part’s cooling rates post-curing. Other equipment is involved but consumes less energy compared to these key units.

5.1. Identify

The initial stage of identifying residual energy began by defining the manufacturing scope, as detailed in Section 4.1. This focused the assessment on energy consumption directly related to the production process. The regressive identification method was chosen due to the project team’s deep understanding of the manufacturing process, including its steps, machinery, and energy demand points. This method involved a backward analysis of the system’s energy emissions, allowing for a comprehensive identification of potential areas of residual energy.

Residual energy for reintegration was identified during the curing phase at the mold, where significant thermal energy is emitted into the manufacturing area. This phase is the most substantial energy consumer in the process, making it a key focus for cost and efficiency improvements. However, isolating the mold faces poses challenges due to the need for workforce access during the manual layup of carbon fiber. The residual energy has a high temperature difference compared to ambient room temperature, making it more usable without further transformations.

Reintroducing this residual heat is also significant for air conditioning, even though it is outside the defined production system scope in this case study. The area is fully air-conditioned due to the handling of pre-impregnated carbon fiber material, meaning the heating process operates in contrast to the air-conditioning system when active.

5.2. Assess

5.2.1. Quantify

In the “Quantify” sub-phase, the identification of residual energy from mold heating revealed a consistent form of energy emission, primarily as heat dissipating into the manufacturing area. Although precise quantitative values cannot be shared due to confidentiality constraints, it is evident that the emitted energy reaches significant levels, peaking at multiple tens of kilowatts during its most intense phases. This emission is temporally irregular, exhibiting intermittent, swelling patterns. Initially, when the heating process begins, the temperature is low, resulting in relatively low radiation. However, at peak temperature, the loss in energy as residual heat reaches its highest point.

Spatially, the dispersion pattern shows radiation emitted from all surfaces of the heated mold. The mold’s cubic shape results in a cylindrical emission pattern with dome-shaped sides surrounding the mold, predominantly directed upwards, following the fundamental principles of thermodynamics where heat tends to rise.

5.2.2. Reclaim

During the “Reclaim” sub-phase, the exploration of residual energy from mold heating in the RTM process reveals several feasible ways of reintegrating this thermal energy. The identified heat energy, being well-established and collectible, is practical to harness. Aligning this residual energy with the needs of other manufacturing processes, particularly the preheating of resin in RTM, shows a perfect match between the available residual heat and the required energy for resin preheating.

The proximity between the mold and the preheating furnace allows for the implementation of a heat exchanger, such as a heat pipe and extraction cups. This mechanism seamlessly links the mold during curing to the preheating furnace, efficiently utilizing excess thermal energy emitted during preheating and curing to preheat resin for subsequent manufacturing cycles.

5.3. Harness

In the case study’s “Harness” phase, the utilization predominantly centers around the “Collect” and “Recommission” sub-phases. Given the continuous nature of manufacturing and the sufficient surplus of residual thermal energy emitted during mold heating and curing, the need for converting energy forms or storing surplus energy becomes redundant. This specificity in this manufacturing context highlights the relevance of tailoring the phases of the IRRE framework to the unique operational dynamics of the manufacturing process under scrutiny.

5.3.1. Collect

In the “Collect” sub-phase of the “Harness” phase, identifying the specific points of residual energy emission within the manufacturing context is crucial. These emission points are primarily located around the closed mold during the heating phase.

The integration of extraction cups has been designed to seamlessly fit with the mold, ensuring they can be easily attached and detached during the handling of the mold for press loading and unloading. This design does not interfere with the mold’s structural integrity or the quality of the manufactured parts. Additionally, adaptable heat pipes have been incorporated. These pipes are flexible and mobile, accommodating the addition or removal of extraction cups without compromising the energy collection process. This flexibility allows the system to adapt to different manufacturing scenarios and requirements.

To minimize potential downtime during the transition between the heating and cooling phases, the system has been designed for quick and efficient management of extraction cups and heat pipes. This ensures a seamless energy collection process. The overall design prioritizes the efficient collection of residual energy by optimizing the placement and operation of extraction cups and heat pipes to maximize the amount of energy collected and reused in the manufacturing process.

5.3.2. Recommission

During the “Recommission” sub-phase, the primary focus is on identifying the reintegration points crucial for reclaiming residual energy. In this scenario, the preheating furnace used for resin before injection is identified as the key reintegration point. This requires an evaluation of the energy demands and patterns within the process. The thermal energy required follows a swelling pattern, aligning with the specific instance of preheating resin before its injection. To successfully align the reclaimable energy potentials with the energy demands, it is essential that the residual energy, after accounting for transmission, conversion, and storage losses, matches or exceeds the energy needed at the reintegration point. In this case, proper temporal synchronization between the preheating and curing processes ensures an adequate surplus of residual energy. The establishment of an energy reintegration matrix in this context results in a singular 1 × 1 field.

Due to confidentiality constraints, detailed technical aspects and specific numerical values related to the manufacturing processes, such as energy consumption, remain undisclosed. These limitations stem from the proprietary nature of the manufacturer’s production data. However, it is noted that the parts under consideration have a significant fiber content of 41%, which is typical for aircraft manufacturing [70]. Depending on the part’s size, there is a substantial demand for preheated resin. For instance, in this case, a final part weighing around 120 kg includes approximately 71 kg of resin. The resin needs to be heated from the ambient room temperature of 21 °C to the operational temperature range of 50 °C to 80 °C.

The energy required for preheating the resin is determined by multiplying the specific heat of the resin, the amount of resin needed, and the temperature difference. It is important to note that the specific heat of the employed resins is not constant but increases with higher temperatures [71], making the actual calculation non-linear.

5.4. Reuse

In the “Reuse” phase, the groundwork established in the preceding “Harness” phase is solidified. The points of energy reclamation and reintegration identified earlier are thoroughly re-evaluated. In this limited case study, due to the selected regressive approach (Section 4.1), only one reclamation point (emission of residual thermal energy from the mold) and one reintegration point (the preheating furnace for resin) have been identified. The evaluation confirms a positive present value (PV), indicating the project’s feasibility.

The pre-designed energy pathway includes several key steps. Firstly, removable extraction cups are chosen for heat collection from the mold when it is loaded into the press, based on the team’s previous positive experience with this technology. Heat pipes made of insulated copper rods are planned for use due to their excellent heat transmission capabilities, and since both processes are located close to each other, this system is efficient. As both the reclaimed and required energies are thermal, there is no need for conversion or storage systems. Plans include installing a copper heat exchanger and a fan within the insulated preheating furnace to enhance heat transfer efficiency through convection.

The documentation includes an energy pathway re-evaluation report, although specific numbers cannot be disclosed due to corporate intellectual property concerns. Additionally, system planning documentation and reintegration strategy overviews are compiled in simplified formats, considering the limited scope of this case study and its lack of interoperability with broader production systems.

5.5. Validate

The “Validate” phase involves post-implementation validation of the modifications made to the production system as defined during the “Identify” phase. Following the completion of these modifications, the adjusted process in this case study was run for a designated period to collect essential data and resolve initial issues.

The primary focus was on examining established performance metrics to assess the effectiveness of the energy reclamation system. Observations indicated that, with adherence to revised work orders, the system operated effectively. Efficiency analysis demonstrated that the system functioned during regular operations without using principal energy for preheating resin, except during the initial start-up phase each day, where resin preheating using principal energy remained necessary since no initial curing was taking place simultaneously.

Technological assessments highlighted the successful functioning of extraction cups but underscored the importance of precise mounting for optimal energy conduction between the mold and cups. Economic viability was gauged through a cost–benefit analysis, which showed a positive present value (PV). However, the positivity was slightly lower than anticipated, attributed to increased costs from necessary work order modifications and occasional lapses in the proper placement of extraction cups, leading to scheduling delays due to unfinished preheating after the curing of the previous part. The overall financial benefit is believed to be higher due to the energy savings for air-conditioning at the vicinity level, which was purposefully excluded during the “Identify” phase.

For the environmental impact assessment, while emissions were reduced due to the absence of principal energy, precise data on resin usage remained undisclosed for intellectual property reasons. Regarding system reliability, extensive testing for ensuring resilience to various process flow alterations and scheduling changes has yet to be conducted. Changes in production schedules might notably affect the system’s effectiveness, especially if the simultaneous execution of part curing and resin preheating is disrupted.

The successful functionality of the energy reclamation attempts in practical operation underscores the effectiveness of the strategies employed. Extensively leveraging the IRRE framework from the project’s inception played a pivotal role in ensuring this successful outcome, leading to plans for its application in evaluating additional processes within the same production plant.

6. Discussion

The IRRE framework appraised has been proven to effectively pinpoint and reintegrate residual energy within definite production systems, showcasing its robustness and efficacy. Its usage can be instrumental in not only identifying but also seamlessly reintegrating residual energy, leading to improvements in process efficiency and heightened energy productivity. Beyond the eco-friendly aspects, the framework can be pivotal in augmenting the overall value proposition of production systems. Its adaptability is meant to span across diverse industries and production scales. By harnessing energy reclamation techniques embedded within the IRRE framework, production systems undergo systematic enhancements via incremental changes, ensuring methodical progress within the economic constraints of the manufacturing domain. The framework’s core focus on financial viability emphasizes its commitment to yielding positive outcomes, navigating toward cost-effective solutions and heightened operational efficiencies likewise. This comprehensive approach firmly positions the IRRE framework as a potent instrument for optimizing energy usage, instigating sustainable advancements across varied industrial landscapes. The framework offers the opportunity to increase the efficiency of processes and thus improve energy productivity.

Still, the IRRE framework’s applicability beyond a large-aircraft industry scope remains unproven. Its validation across diverse sectors is outstanding. While the framework adeptly deconstructs problem contexts at a high level, its execution necessitates a diverse toolkit tailored to each phase. Tools sourced from the adopters’ corporate manufacturing toolset or literature must be validated for themselves beforehand to ensure their contribution to the IRRE framework’s overarching objectives. Notably, the framework’s energy efficiency focus primarily addresses energy loss attributed to the “lack of recovery” as outlined in Figure 1, arrow 8. However, achieving comprehensive energy efficiency mandates addressing all other loss aspects, demanding supplementation by further specialized tools. The potential of the production system and its machinery, coupled with energy data gaps and the ambiguity surrounding potential conversion devices, present challenges in fully grasping and optimizing the system’s intricacies. These complexities underscore the need for enhanced data collection and a deeper understanding of conversion devices to realize the framework’s holistic potential.

7. Outlook

In advancing the framework’s validation, future research should expand use cases to encompass other industries and manufacturing scenarios. This extension offers an evaluation scope spanning both brownfield and greenfield approaches, to which the framework might also be applicable. Diverse industrial processes across varying production rates must be considered, forming the foundation for evaluating the framework’s efficacy in differentiating amortization rates. This is pivotal for confirming the framework’s applicability across industries and production contexts, proving its adaptability and relevance in diverse operational landscapes. Potentially, the framework described here could also be suitable for other areas such as energy generation or mobility, e.g., gas turbines and combined heat and power plants. This has not yet been considered, and further research is needed to evaluate this potential.

To ensure the continuous relevance and effectiveness of the ECO table from Section 3 as a valuable tool, it is imperative to establish regular updates. The table’s evolution should align with the advancements and innovations in energy conversion systems, incorporating additional specific systems and comprehensive cost estimates for energy conversion. This expansion not only enhances the tool’s comprehensiveness but also facilitates a swifter evaluation of return on investment. By incorporating cost data, the ECO table can provide a more dynamic and responsive assessment, enabling decision-makers to gauge the economic viability of energy reclamation initiatives more promptly.

Moreover, the tools mentioned within the framework’s phases for detailed assessments and task elaboration necessitate further exploration and analysis within the context of this framework in future research. Demonstrating these tools in different operational contexts in the light of the IRRE framework will be vital for proving the framework’s industrial applicability. A more comprehensive exploration, encompassing economic and industrial viability, might foster the creation of integrated systems that not only recycle materials but also efficiently capture and repurpose diverse energy forms. Future research should focus on the deduction of an integrated efficiency toolset incorporating both energy and material streams to decrease production systems’ environmental impact.