Impact of Weak Signals on the Digitalization of Risk Analysis in Process Safety Operational Environments

Abstract

Weak signals in risk analysis digitalization are of great importance for preventing major accidents in risk analysis in the process industry, especially for process operations and production. However, some of the negative impacts are incorrect operational risk identification, significant inventory carrying costs, disruption of risk frequency, and risk consequence analysis, all of which will signal inaccurate information about unforeseen and current dangers in process facilities and operational environments. While the positive impacts are viewed as an early warning system that provides information on operational risk system status, the identification of potential risk weaknesses in process facilities, indicators of a transition or an emerging problem that may become significant in the future, highlighting future assumptions, challenge our views of the future and expand the selection of a processing facility. Lastly, weak signal identification in the digitalization of risk analysis can provide relevant information in supporting, assessing and analyzing the risks associated with the operation, in order to design a technical system and estimate the industry’s level of accident risk, as well as the possible control of a system. The present research will provide valuable information to the process industry on how to protect their operational facilities and increase process safety by providing information on weak safety risk monitoring systems in operations, strengthening the processes of the operational area.

1. Introduction

The definition of signals, in general, is a broad one. It can be applied to almost any situation. It is critical to receive warning signs on time to prevent severe accidents and to be able to eliminate any potential accidents with unanticipated consequences Argyropoulos et al. [1], Nivolianitou et al. [2]. Furthermore, process industries frequently work with hazardous chemicals, substances, and processes, substantially raising the risk of operational catastrophe in their activities Khan and Abbasi [3], Khan et al. [4]. Moreover, the process industry is operated under potentially hazardous conditions of very high/low pressures and temperatures, respectively, which can generate significant risk to the facilities Rigas and Amyotte [5], Abbasi et al. [6], Argyropoulos et al. [7].

Despite the advancements in the field of process safety and technology, notable incidents in the process industry continue to occur, possibly due to the presence of weak signals. However, these weak signals are known to be unidentified, ignored, or misinterpreted, which can lead to future occupational or industrial accidents Nicolaidou et al. [2].

Weak signals were initially defined by Ansoff and McDonnell [8], within the context of business environments, as an “…imprecise early indication about impending impactful events… all that is known is that some threats and opportunities will undoubtedly arise, but their shape and nature and source are not yet known…symptoms of the possible change in the future”. considerably enhanced Ansoff’s definition by describing their main characteristics:

■

“An idea or trend that will affect the business or business environment”;

■

“New and surprising from the signal receiver’s vantage point, although others may also perceive it”;

■

“Sometimes difficult to track down amid other noise and signals”;

■

“A threat or opportunity to an organization”;

■

“Often scoffed at by workers who ‘know’”;

■

“Usually has a substantial lack time before it will mature and become mainstream”;

■

“Therefore, represents an opportunity to learn, grow and evolve”.

It is noteworthy that the above-mentioned characteristics can be similarly used within occupational environments Nicolaidou et al. [2].

The importance of weak signal management in industrial safety problems was first identified by high-reliability organizations, who considered weak signals as early alerts of potential incidents that could become catastrophic Koivisto et al. [9].

Despite the lack of testing and validation reports, a weak signal management procedure for the workplace has been developed, with limited applications to report within the occupational environment Brizon and Wybo [10], Nicolaidou et al. [2].

In general, the application and use of weak signals in the OSH domain are underutilized. There also appears to be a lack of a concrete understanding or widely accepted definition of weak signals, explaining the lack of a systematic approach to their management. For example, some warning signals can suggest unexpected discontinuities in production facilities Nicolaidou et al. [2].

However, such signals or information about probable future malfunctions, according to Webb [11], could not be retrieved, and Ansoff and McDonnell’s [8] work had no prior basis to support such claims. They believed that weak signals could only convey insufficient information about the final potential threat.

According to Ashley [12], such discontinuities are only seen after they have occurred. Furthermore, according to Makridakis and Heáu [13], the concept of weak signals has remained a highly relevant academic term, and weak signals are typically so imprecise that they are readily missed. As a result, believing in them is challenging, due to their ambiguity, irrationality, and credibility.

Furthermore, many other scholars, on the other hand, have used slightly different terminology to express the same underlying notion, such as indicators, early indications, soft forms of information, and early warnings King [14]; Juran [15]. Moreover, some scientists and engineers have undertaken research to explore the presence and impact of weak signals in companies that operate in high-risk environments Leidecker and Bruno [16]; Pinto and Slevin [17]. Moreover, industries with a high level of reliability, such as aerospace, manufacturing, and nuclear power, have recognized the significance of weak signal control. Recognizing weak signals as early warning indicators for the potential risk of accidents could be important for dealing with potential risk.

However, the process industry seems to be unable to detect so-called “weak signals” or process irregularities that could have substantial implications for the digitalization of their process facilities in conducting effective risk assessments Koivisto et al. [9]. Furthermore, some researchers have noted that accurately identifying weak signals and using them to take appropriate steps will prevent technical accidents Brizon and Wybo [10]. While some industries ignore weak signals in the workplace, others use them to learn more about injury prevention and become more proactive in their process activities Kaivo-oja [18].

In addition, apart from recognizing these weak signals as precursors to significant accidents in the process operation, other explanations could be attributed to the limited analysis capabilities of process safety techniques, resulting in insufficient control over potentially hazardous processes Knegtering and Pasman [19]; Le Coze [20], Chang et al. [21]. Early recognition of these “weak signals” in risk engineering analysis has also played a significant influence in improving the efficiency of risk monitoring in the process industry Ilmola and Kuusi [22], as well as the efficacy and safety of process operations Aven [23]; Benson et al. [24].

According to the National Academy of Engineering’s Annual Report NAE [25], weak signals may also be precursors, describing precursors as “the circumstances, events, and sequences that precede and lead up to an accident”. Furthermore, prior accidents have also been known to have ignored signals and alarms that might prevent the adverse incident from occurring if properly detected and monitored Taylor et al. [26]. By using warning alarm indications and digitalized equipment (automatic data collection), risk engineering can also help with process evaluation and production processes and procedures Parviainen et al. [27]; Paltrinieri et al. [28]; Schmitz et al. [29]; Sharmin et al. [30].

Moreover, monitoring accident precursors, such as “weak signals” along with evaluating the causes, can be very useful for developing knowledge and experience to achieve an appropriate degree of safety competence. They highlight safety system weaknesses without having significant adverse effects, resulting in more successful accident prevention Andriulo and Gnoni [31]. Additionally, when combined with better representations of risky situations, precursors may prove to be quite effective tools for managing various risks, and their evolution over time Jean-luc et al. [32].

In summary, the process industry would benefit from considering weak signals in the digitalization of risk analysis in a process safety operational context. This involves identifying potential risks in process facilities, and identifying indicators of a transition or an emerging problem that may become significant in the future.

The purpose of this research was to identify the impact of weak signals on the digitalization of risk analysis in process safety operational environments. The rest of this paper is organized as follows: Section 2 provides an overview of the concept of process safety digitalization, accidents, and weak signals; Section 3 outlines the impact of weak signals on digital process control systems; Section 4 outlines the impact of weak signals on the process safety risk analysis digitalization method. Finally, the conclusions of this research are presented in Section 5.

2. Concept of Process Safety Digitalization, Accidents, and Weak Signals

Process digitalization refers to the integration of new technologies into existing processes to improve productivity and product quality. It can also record and convert analogue signals into digital representations that can be understood and delivered electronically. However, process digitalization is becoming more commonly embraced in industrial processes, and it has the potential to improve the chemical process industry’s efficiency, flexibility, and quality. Moreover, process digitalization will significantly change at both the process and organizational levels due to its fundamental implementation of modern technologies Benson et al. [24].

Additionally, one of the advantages of digitalization is the production of current technologies, such as digitized operational data and the replacement of manual process operations with software, which allows for automated data gathering for effective process monitoring Parviainen et al. [27]. Processes are thus tracked and managed in a digitalized environment for increased efficiency and performance Fazai et al. [33].

Furthermore, new technologies have the potential to push beyond conventional control systems. In the process industry, rates of availability are often the most critical factors to consider. Asset condition, process quality, and throughput can all be better monitored with digitalization. Digitalization allows for rapid intervention to avoid errors and reduce expensive output when used in conjunction with actual-time and predictive modelling. However, the digitalization of process operations, on the contrary, has a substantial adverse effect on operating environments and process equipment Benson et al. [24], Dai et al. [34]. Moreover, the digitalization of process safety operations started with major industrial accidents, such as those of Flixborough (1974), United Kingdom, Seveso (1976), Italy, Bhopal (1984), India, and Piper Alpha (1988), United Kingdom, among others, between 1960 and 1990, as a result of rapid industrialization and technological transition Kletz [35]; Macza [36]; Weick [37]; Planas et al. [38], Benson et al. [24].

These industrialization and technical revolutions in the process industry identified one component that played a significant impact in several process-related incidents. This element was named to be a weak signal. These weak signals are a type of data that pertain to a possible change in the device under investigation and travel in an undetermined direction. They are the first signs of significant changes, warning signs, or potential opportunities Heinonen et al. [39]; Hiltunen [40]. Weak signals, in the first instance, can be amusing or frightening, and they can be perplexing because they often include new ideas and innovations or ways of thinking Heinonen et al. [39]. Moreover, some industrial incidents linked to weak signals have been investigated.

One accident took place in Bhopal 1984 [India], Broughton [41]; Eckerman [42], which occurred when about 45 tons of the gas methyl isocyanate escaped from a plant. The causes of the Bhopal accident have been extensively investigated. However, in the accident reporting and analysis phase, neither of the authors of these studies (or other research looking at the same event) used the term “weak signals”. However, a closer examination revealed a slew of instances that exactly matched the theory in question.

In the Chernobyl accident (1986) report literature, “weak signals” are not treated or categorized as a separate safety concept Malko [43]. However, a closer look at the information shows a lot of operational events that “fit” the general concept of a “weak signal.” The failure of three tests before the catastrophe to evaluate the safety valves’ capacity to function with the backup generators and to transfer water to cool the system in the event of a power outage and, as a result, overheating, is a typical case of a weak signal in terms of operation. The same incident demonstrates the operational existence of weak signals. The workers about to run the final test had no clear instructions on how to conduct it, and the young inexperienced senior engineer had only been in this position for three months Malko [43]; Wilson [44]; Martnez-Val et al. [45].

Piper Alpha’s tragedy in 1988 had such a significant human and social impact that it triggered an extensive and detailed public inquiry, leading to Cullen’s popular report in 1990 Cullen [46]. Furthermore, many experts have investigated the disaster’s root causes from different angles Singh et al. [47]; Shallcross [48]; Broadribb [49]. Significant weaknesses in the work permit, firefighting, and safety-training programs were highlighted in the Cullen study. Defects relating to erosion and corrosion were also addressed as “second-tier” issues Singh et al. [47]. The results of the Cullen study, which investigated the world’s worst offshore disaster, have significantly changed offshore platform safety standards and procedures Broadribb [49].

However, reported studies on Piper Alpha revealed a lot of “signals” that were either ignored or misinterpreted before the disaster. Specifically, the engineer of Piper Alpha’s morning shift, despite noting in the work permit that the maintenance job was not completed, transferred to the control room following the change in operations, causing the incident Nicolaidou et al. [2]. Additionally, weak operational signals found in the Piper Alpha accident investigation reports did not appear to be one-off incidents in general. Regrettably, all such “signals” discovered during audits were rarely recorded or handled.

In the Deepwater Horizon tragedy, weak signals were also discovered (2010). In 2010, President Barack Obama established an impartial National Commission to investigate the causes of the Deepwater Horizon disaster. The conclusions were published in a report by the National Oil Spill Commission [50]. The Deepwater Horizon Marine Casualty Investigation Report Republic of the Marshall Islands [51] produced by the Marshall Islands’ Marine Administrator, also provided valuable information. Several academic scholars have since contributed to the academic literature on the disaster’s causes, such as Espen and Vinnem [52]; Wolf [53]; Rathnayaka et al. [54], among others. However, cement slurry instability signals, on the other hand, were discovered twice. Still, no further investigation was conducted, resulting in incorrect cement slurry stability design and indications of the well not being sealed. The risk of a blowout in the well was ignored Reader and Connor [55].

Additionally, on 11 December 2005, an overfilled fuel (gasoline) storage tank at the Buncefield oil storage facility in the United Kingdom was caused by the breakdown of an automatic tank measuring system. The alarm, for example, was unable to send signals to control systems, which was thought to be interfering with the weak information Argyropoulos et al. [1,56,57], Markatos et al. [58]; Paltrinieri et al. [28].

3. Impact of Weak Signals on the Digital Process Control System

The Digital Process Control System (DPSC) monitors, manages, nominates, schedules, dispatches, and reports all actions occurring in processing facilities for effective and efficient operations. Processing plants (PP) convert natural resources such as crude oil and natural gas into various products for human and economic consumption, and process control systems have many components that make the operations easier for operators. However, these components are affected by a factor called weak signals. These weak signals form a barrier between the DPCS and PP in sending and receiving a message to the operational environment. Figure 1 presents the impact of weak signals on digital process control systems.

A component, such as a Digital Pressure Monitoring Alarm (DPMA), monitors the pressure of the moving fluid in the flow line during the batching process. However, if the signals sent from the process control system to the process plant were not supported due to interference of external bodies known as weak signals, this could lead to pressure build-up in the pipeline. Moreover, when there is an overpressure or pressure build-up in the flow line this will lead to an incident, such as an explosion, in the pressure gauge equipment and fluid storage tank. In processing plants, the Digital Control Production Valve (DCPV) is a crucial component. DCPV receives a signal from the control system and uses it to control the flow of processed products in and out. Moreover, the DCPV will be automatically activated when a signal is received. In case where the signals present are weak or have been interfered with, this might result in accidents such as fluid overflow in the flow line, the flooding of processed products in the operational environment, and explosions, among others. Digital Fire Monitoring Alarms are applied to monitor the Digital Processing Sensing Line (DPSL) and unusual events in operation facilities.

Poor line sensing information and the deactivation of fire monitoring alarms in the process plant will result from the DPSL and DFMA’s weak signals. In addition, digital machinery health monitoring (DMHM) has a place in the plant; it aids in detecting early signs of anomalies, diagnosis vibration, and lubrication issues. The Digital Products Leakage Monitoring Alarm (DPLML) provides a warning for the potential for fires, explosions, and unintentional releases of harmful chemicals in petrochemical refining oil and gas production facilities Benson et al. [24]. Furthermore, operational control entails the oversight of the site manager, who directs the staff to follow workplace safety regulations.

Consequently, weak signals in the digital process operation will disrupt the process, resulting in process component malfunction and breaches of information from the control process system. Some of the negative impacts of weak signals present in the digital process control system: shutting down operations which will lead to losses in production, the irregular warning of alarming devices, inadequate data gathering in the risk assessment process, and an unbalance in the product batching process Benson et al. [24]. The positive impact of weak signals is that they are advanced warning signs, meaning that operators can be proactive in responding to any risk, ensuring that an operating plant and its surroundings are adequately protected. Moreover, they provide appropriate information on an area of weakness in the safety monitoring system of the process facilities.

4. Impact of Weak Signals in the Process Safety Risk Analysis Digitalization Method

Many industries have not updated their risk analysis processes in many years; instead, they rely on manual review processes for monitoring risks. This system can be slow, it involves duplication and redundancy across various departments in the operational environment, and it leaves a lot of possibility for human error. However, threats may not be recognized in a timely way, potentially resulting in safety breaches and other risks that could have been avoided if the risk had been digitalized and analyzed in the process operation Benson et al. [24].

A significant instrument for developing strategies of preventing accident risk and mitigation measures is risk analysis using a digitalization method. Due to the issues in safety measures originating from the undesired operational area, it is critical to use a digitalized risk analysis in process operations. Using a digitalization strategy for risk analysis will aid in detecting potential hazards, as well as measuring and analyzing the risks associated with the operation design and technical system errors. Estimating the level of accident risk is also important. In operational facilities, risks such as fire, explosion, and toxic substance spills can be digitalized and monitored Aven [23]; Benson et al. [59].

In addition, one of the goals of this risk analysis digitalization approach is to manage risk and ensure acceptable industrial safety in the process facilities and operational area. Consequently, the digitalization of risk analysis is seen as the avoidance or elimination of negative outcomes. This safety approach follows the credo of improving safety by learning from errors and accidents. Moreover, organizations with this expertise may be able to learn from previous occurrences, but they are unlikely to be able to predict future dangers due to interference from weak signals. These weak signals, on the other hand, have been found as having both negative and positive effects on the process industry’s digitalization approach to risk analysis.

Furthermore, some of the negative impacts of weak signals include incorrect operational risk identification, significant inventory carrying costs, disruption of risk frequency, and risk consequence analysis, all of which will signal inaccurate information about unforeseen and current dangers in the process facilities and operational environment. While there are positive impacts of an early warning system that provides information on operational risk system status, there are also potential risk weaknesses in process facilities, such as indicators of a transition or an emerging problem that may become significant in the future, highlighting future assumptions, challenging our views of the future, and expanding the selection of alternate futures Kayikci [60]. Figure 2 depicts the impact of weak signals in the process safety risk analysis digitalization method.

Identifying and utilizing risk is one of the most pressing challenges in the process environment. However, the digitization of risk is one of the strategies offered to reduce operational risk. Despite this, interference from “weak signals” has been identified as a barrier to the digitalization of operational systems and risk assessments. Guidance on safety integrity levels and layer of protection analysis (LOPA) AIChE [61], based on IEC 61,508 and 61,511 standards, define instrumented System (SIS) and Safety Instrumented Functions whenever a system deviates from its regular operations (SIF). Sensors, logic controllers, and actuator devices make up the (SIS) system. Data from the activity sensed by sensors (such as temperature, pressure, or flow data), and logic controllers (PLCs, DCSs, or any microprocessor-based device) are at the heart of the system processing operational data, while actuators monitor valves and indicators Wang and Rausand [62].

The weak signal interferences on the SIS, on the other hand, will result in insufficient sensations from the instrument utilized to monitor various parameter functions in processing facilities. Safety shutdown mechanisms are another name for SIFs. The SIF system consists of sensors and logical servers. Its responsibilities include monitoring changes in process operations and allowing a process to continue safely when a risk condition is detected. Furthermore, identifying and detecting unsafe operations will not be ascertained as a breach of signals between SIF and processing facilities, leading to unplanned equipment shutdown operations. However, if the facility shut down, facility operations would be severely limited, resulting in substantial production losses, economic losses, and damage to equipment.

The second phase of risk digitalization involves significant risk identification in the operational environment, such as evaluating fire risk, explosion, leakage of toxic fluid, accidents, operating system failure, and other potentially harmful events that could disrupt process operations. However, the risks might not be identified in the operating system because there are no proper signals received from the OSD, because of the breach of signals with operational components that are supposed to capture and release the information of an existing risk. Additionally, when the risk is not captured due to the weak signal, the risk remains unseen or blind, which could be identified later when an accident has already occurred in the processing facility.

Risk frequency estimation is the third phase of the digitalization of risk analysis (RFE). It determines the likelihood that the detected hazards will be detrimental to workers or facilities. It takes into account the severity of all recognized dangers in a working environment, such as fire, explosion, hydrocarbon leakage, and accident, as well as the likelihood that the detected risk may affect workers. Additionally, the third phase of the risk digitalization will not be actualized because the risk information on existing threats is not correctly identified and examined due to the misinformation of signals. Estimating the frequency of unseen risks is challenging; one can only calculate and analyze seen risks.

The fourth phase is the Risk Consequence Estimate (RCE). This defines risk in a chain of consequences based on the release details of the compared risks. Moreover, it creates quantitative values indicating the risk effects on workers, equipment, and the overall operational environment. Risks are analyzed to see if they are within acceptable levels or not. Furthermore, risk acceptability proceedings necessitate the specification of risk values that constitute the acceptability threshold Trbojevic [63]. Before any accident or catastrophe, a final decision or approach is made to either eliminate, mitigate, or track the impact of known risks associated with a specified activity.

The final phase of risk digitalization analysis is risk control measures (RCM). Considering the managed effect of underlying risks in the process, this measure looks at the possibility of thoroughly monitoring risks in the system, either by technical controls, administrative measures, or personal protective equipment (PPE). Furthermore, managing risks arising from the operational environment may be difficult, because receiving signals may have provided incorrect information on existing risks, resulting in a misunderstanding of the method to be used to address the threat from the operational area. Some of the capabilities of risk analysis digitalization also help with operational hazards. Virtualization, which eliminates the need for the step-by-step transcription of errors, also aids in the copying of factor information between equipment and SIFs, lowering the cost of functional safety engineering. Risk analysis digitalization approaches can also be predicted and dealt with in process operations and other related industries that operate in a high-demand environment.

5. Conclusions

The goal of this study was to investigate the impact of weak signals on risk analysis digitalization in the operational environment, as well as to provide useful information on how weak signals affect facility and process safety operations. In this research, we realized that weak signals are highly relevant to the digitalization of risk analysis, and can provide information on industrial risks such as fire, explosion, and toxic release to the environment, as well as disruption to operational facilities.

In addition, there can be disruptive changes in the operating environment of the process safety activity caused by weak signals. All of these changes can be translated into success, even though digital transformation is a monumental and multi-dimensional concept. Weak signals will provide ongoing automated risk assessments in the process industry for identified risks based on monitored risk indicators. For example, one key risk indicator might be the percentage of scheduled maintenance activities, such as software patching, not taking place as they should have—if this number goes above a set threshold, this could be considered an operational risk. Thus, the system will send out an early warning signal to the relevant managers.

Furthermore, weak signals focusing on the digitalization of risk analysis method have been identified to have had negative and positive impacts on some of the industrial accidents that occurred in 1960 and 1990, such as Flixborough (U.K.), Seveso (Italy) and Bhopal (India), among others. Some of the negative impacts were incorrect operational risk identification, significant inventory carrying costs, disruption of risk frequency, and risk consequence analysis, all of which signaled inaccurate information about unforeseen and current dangers in the process facilities and operational environment. The positive impacts included: being viewed as an early warning system providing information on operational risk system status; the identification of potential risk weaknesses in process facilities; being indicators of a transition or an emerging problem that may become significant in the future; highlighting future assumptions, challenging our views of the future, and expanding the selection of a processing facility.

Moreover, weak signal identification in the digitalization of risk analysis has provided relevant information for supporting, assessing, and analyzing the risks associated with operations, as well as offering the design of a technical system to estimate the industry’s level of accident risk, and possible control. The findings of this research identified valuable information on weak signal impacts on risk analysis digitization in processing facilities and operational areas. If weak signals in the process industry are detected earlier and managed properly, accidents and risks in operational processes can be reduced, and ineffective monitoring systems and risk analysis digitalization can be strengthened.