Industry 4.0 as an Opportunity and Challenge for the Furniture Industry—A Case Study
Abstract
:1. Introduction
2. Theoretical Background
2.1. Smart Factories and Industry 4.0
2.2. Integration of Industry 4.0 into Smart Factories
2.3. The Basic Building Blocks of Industry 4.0
3. Methodology
4. Results
4.1. Case Study—Complete Integration of Industry 4.0 into the Furniture Industry Based on the 7S Model
4.1.1. Structure
- Pre-production department: sales, design, development, accounting, construction, and warehouse;
- Production department: engine room (material cutting, banding, and CNC), other engine room, paint shop, pressing shop, and handicraft workshop;
- After production department: shipping, assembly, and logistics.
4.1.2. Strategy
4.1.3. Systems
4.1.4. Management Style
4.1.5. Collaborators
4.1.6. Competences and Skills
4.1.7. Shared Values
4.2. Technological Components of Industry 4. 0—Intelligent Factory
Main Building Blocks of Industry 4.0
5. Discussion
Industry 4.0 vs. Industry 5.0 (from Digital Production to a Digital Society)
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
CPS | cyber–physical systems |
HCPS | Human–Cyber–Physical System |
EC | European Commission |
AI | artificial intelligence |
MES | manufacturing execution system |
ERP | enterprise resource planning |
ICT | information and communications technology |
IoT | Internet of Things |
IoS | The Internet of Services |
RFID | Radio Frequency Identification |
CM | Cloud manufacturing |
CC | Cloud computing (CC) |
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Type | Basic Characteristic | Example |
---|---|---|
(1) Internet of Things (IoT) | A network infrastructure that provides data transmission and sensor collection. The data collected are mostly difficult to measure by human perception, and then sent over the network. | A computer network that exchanges information between computers and provides data transmission and communication, for example, through M2M, which transforms human–machine dialogue. Using various sensors, transducers and sensors, the data are measured and transmitted to the cyber environment via the Internet. The collected information is difficult to measure by man, such as smoke leakage, vibration, product defects, weight, roughness, temperature, movement and more. The obtained information is evaluated directly by a sensor, which is also capable of making simple decisions or send data to collection points (cloud storage). Based on specific events, various cameras, sensors can be used to monitor the service life and predict the maintenance of machines, which reduces service costs, increases product quality, increases machine safety and more. |
(2) Internet of Services (IoS) | These are software solutions stored on networks and cloud storage, for example. It creates predefined operations or decisions based on the data flow or a certain programmed trigger impulse. | Their purpose is to compile reports, monitor the performance of individual departments, support the motivation and retraining of employees and more. Software operating on networks or repositories performs repetitive processes and evaluates any pre-programmed tasks. Furthermore, the SW can perform predefined control tasks on the basis of the evaluated data, it can also start or set other devices. Examples are software that controls a company’s safety systems, production-quality robots that control the production flow, machining speeds, and more. |
(3) Intelligent factories | Comprehensive factory management to reduce errors and increase efficiency. | Autonomous information exchange and monitoring of business activities. For example, it is an Intelligent Ordering and Payment System through an intelligent platform. Thanks to information from the network, we can, for example, “immerse” ourselves inside machining centres and thus obtain data on a given date and time of the performed activity, where we can monitor the efficiency and think about innovations. It is comprehensive coverage of the production and non-production operations within a smart company. |
(4) Human–Cyber–Physical Systems (HCPS) | Based on the use of cyber–physical systems to create self-organising structures. Teams are made up of human resources and software that creates organised units. | CPS refers to a system that consists of physical resources controlled by computer algorithms. Through CPS, Industry 4.0 increases the ability to communicate with machines, while managing the production and machine capabilities. In practice, information on all phases of furniture production, such as design, production, logistics, transport, machine maintenance and more, is linked through the CPS where it is not natively provided by the supplier. In practice, all the manufactured parts are marked with bar/QR codes, after the code is read by the sensor by any production device at the input and output, there is a reference to the records of all the data in the cloud storage. One can enter this process, for example, using the machine’s display, tablet or other display devices and modify the process itself depending on one’s own decision. A machine, program or machine learning together with a person can thus create a work team or organisational unit. |
(5) Big Data | Huge amount of all company data, related to each material or intangible segment forming a product or production segment | The intelligent factory is characterised by its communication network, allowing detailed monitoring of all the processes using a variety of sensors ensuring large data collection and distribution, which are: inspection of machines and their operation, monitoring of service life, and the influence of the environment or materials in interaction with various tools and other production aspects. The data from the machine or production technology are sent in a raw or pre-processed state to cloud repositories. |
(6) “Cloud manufacturing” (CM) Cloud computing (CC) | Cloud storage focused on network services, storage of large data in a raw or pre-processed state, current and predictive evaluations and comprehensive conclusions across the enterprise. Internal servers can also be used, backed up if possible. | In the cloud storage, the data are evaluated. The data obtained this way are aimed at more efficient management, planning and optimisation of production and evaluation of predictable situations across the entire plant. By collecting and evaluating data, the system can predict any failure or worn tool. The data provided can indicate, for example, increased temperatures or higher machine vibrations. These and other collected data make it possible to anticipate machine failures, and defective parts, or to point out the low efficiency of various segments of the company and thus create a more efficient and sustainable process. |
(7) Cyber Security | Safety in the area of Personal Data Security | This is the security of data transmission and management in the communication network and across the services used. It is the direct and indirect protection of the companies and their cloud storage. Company data are centralised in the company in cloud storage outside the company or on its own backup servers. This service is offered by specialised companies, which provide special protection here. The data are encrypted and unreadable to the average user. By indirect protection, we reduce the leakage of sensitive and valuable information through user authorisations and processes to restrict document accessibility, censor sensitive information, and unauthorised physical copying outside the enterprise. |
(8) Autonomy or artificial intelligence (AI) | Use of artificial intelligence to streamline production lines with the participation of human resources | More human resource opportunities for personal development and space for innovative thinking. For example, the application of newly designed strategies obtained through the evaluation of analysis and machine learning with the participation of human resources and their experience. Based on the collection of relevant data, these data are subjected to a statistical analysis, which serves to streamline production and previous order preparation. |
(9) Servitisation, servification | Creating a direct interaction between the primary manufacturer and the customer | Vision of future furniture production aimed at the customer, by connecting Internet marketing together with smart automated production and order processing. The product will be manufactured after direct order by the customer. All this leads to more flexible production, with zero or minimal stock. For example, the design of parametric products will help increase the added value of processing, satisfy individual demand, and reduce the cost of activities associated with the preparation of production. An example is the possibility of creating user-friendly software, where the client designs his own specific furniture with the possibility of consulting corporate architects. The said furniture would then be automatically produced after the required deposit has been paid, without a significant entry of employees into production. The customer thus directly participates in the pre-production part, while the production itself takes place fully automatically. |
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Červený, L.; Sloup, R.; Červená, T.; Riedl, M.; Palátová, P. Industry 4.0 as an Opportunity and Challenge for the Furniture Industry—A Case Study. Sustainability 2022, 14, 13325. https://doi.org/10.3390/su142013325
Červený L, Sloup R, Červená T, Riedl M, Palátová P. Industry 4.0 as an Opportunity and Challenge for the Furniture Industry—A Case Study. Sustainability. 2022; 14(20):13325. https://doi.org/10.3390/su142013325
Chicago/Turabian StyleČervený, Luboš, Roman Sloup, Tereza Červená, Marcel Riedl, and Petra Palátová. 2022. "Industry 4.0 as an Opportunity and Challenge for the Furniture Industry—A Case Study" Sustainability 14, no. 20: 13325. https://doi.org/10.3390/su142013325