Smart control of the assembly process with a fuzzy control system in the context of Industry 4.0

Assembly line balancing is important for the efficiency of the assembly process, however, a wide range of disruptions can break the current workload balance. Some researchers explored the task assignment plan for the assembly line balancing problem with the assumption that the assembly process is smooth with no disruption. Other researchers considered the impacts of disruptions, but they only explored the task re-assignment solutions for the assembly line re-balancing problem with the assumption that the re-balancing decision has been made already. There is limited literature exploring on-line adjustment solutions (layout adjustment and production rate adjustment) for an assembly line in a dynamic environment. This is because real-time monitoring of an assembly process was impossible in the past, and it is difficult to incorporate uncertainty factors into the balancing process because of the randomness and non-linearity of these factors. However, Industry 4.0 breaks the information barriers between different parts of an assembly line, since smart, connected products, which are enabled by advanced information and communication technology, can intelligently interact and communicate with each other and collect, process and produce information. Smart control of an assembly line becomes possible with the large amounts of real-time production data in the era of Industry 4.0, but there is little literature considering this new context. In this study, a fuzzy control system is developed to analyze the real-time information of an assembly line, with two types of fuzzy controllers in the fuzzy system. Type 1 fuzzy controller is used to determine whether the assembly line should be re-balanced to satisfy the demand, and type 2 fuzzy controller is used to adjust the production rate of each workstation in time to eliminate blockage and starvation, and increase the utilization of machines. Compared with three assembly lines without the proposed fuzzy control system, the assembly line with the fuzzy control system performs better, in terms of blockage ratio, starvation ratio and buffer level. Additionally, with the improvement of information transparency, the performance of an assembly line will be better. The research findings shed light on the smart control of the assembly process, and provide insights into the impacts of Industry 4.0 on assembly line balancing.     

Understanding the implications of digitisation and automation in the context of Industry 4.0: A triangulation approach and elements of a research agenda for the construction industry

In recent years, Industry 4.0 has been introduced as a popular term to describe the trend towards digitisation and automation of the manufacturing environment. Despite its potential benefits in terms of improvements in productivity and quality, this concept has not gained much attention in the construction industry. This development is founded in the fact that the far-reaching implications of the increasingly digitised and automated manufacturing environment are still widely unknown. Against this backdrop, the primary objective of this paper is to explore the state of the art as well as the state of practice of Industry 4.0 relating technologies in the construction industry by pointing out the political, economic, social, technological, environmental and legal implications of its adoption. In this context, we present the results of our triangulation approach, which consists of a comprehensive systematic literature review and case study research, by illustrating a PESTEL framework and a value chain model. Additionally, we provide recommendations for further research within a research agenda.     

Industry 4.0 enabling manufacturing competitiveness: Delivery performance improvement based on theory of constraints

Due date control (DDC) can be regarded as one of the competitive abilities of an enterprise. Based on advanced connected technologies implemented in Industry 4.0, DDC can collect processing information accurately and in real time to be integrated with production systems. It is an intelligent event-driven feedback control that can be designed to control process plans. In this study, a work-in-process alert system framework is developed based on a machine-to-machine communication approach. Subsequently, a manufacturer can monitor and perform DDC for each process based on the buffer control of the theory of constraints. The latter is a methodology for identifying the most important limiting factor, such as constraints, that prevents the attainment of a goal and then systematically improves that constraint until it is no longer the limiting factor. Furthermore, using hybrid strategies of Industry 3.5, a material planner can collaborate with suppliers to improve delivery performance. This approach is effective in semiconductor manufacturing.     

Industrial maintenance decision-making: A systematic literature review

The increasing competition among industries has leveraged the emergence of various tools and methods for maintenance decision-making support. This paper identifies in literature the application areas of industrial maintenance decision-making, the relationships between these areas and the ways in which authors integrate tools and methods. This information makes it possible to identify trends and deficiencies in this context, helping to centralize the efforts required for future work. This work follows a series of structured steps for a systematic literature review of papers related to the main topic available in online databases. The selected papers are subject to a content assessment and grouped according to the application areas. The direct comparison between these areas and the construction of a relational matrix provide a quantitative interpretation of the results and well-structured information. Additionally, this paper proposes a framework based on information from the literature, which summarizes the origin and flow of information used in the development of models, showing the relationship among application areas of decision making. The research undertaken identifies trends focused on joint production systems optimization and increasing the deployment of methods for autonomous equipment predictions.     

A Quality 4.0 Model for architecting industry 4.0 systems

The increasing importance of automation and smart capabilities for factories and other industrial systems has led to the concept of Industry 4.0 (I4.0). This concept aims at creating systems that improve the vertical and horizontal integration of production through (i) comprehensive and intelligent automation of industrial processes, (ii) informed and decentralized real-time decision making, and (iii) stringent quality requirements that can be monitored at any time. The I4.0 infrastructure, supported in many cases by robots, sensors, and algorithms, demands highly skilled workers able to continuously monitor the quality of both the items to be produced and the underlying production processes.While the first attempts to develop smart factories and enhance the digital transformation of companies are under way, we need adequate methods to support the identification and specification of quality attributes that are relevant to I4.0 systems. Our main contribution is to provide a refined version of the ISO 25010 quality model specifically tailored to those qualities demanded by I4.0 needs. This model aims to provide actionable support for I4.0 software engineers that are concerned with quality issues. We developed our model based on an exhaustive analysis of similar proposals using the design science method as well as expertise from seasoned engineers in the domain. We further evaluate our model by applying it to two important I4.0 reference architectures further clarifying its application.     

Development of Industry 4.0 predictive maintenance architecture for broadcasting chain

Industry 4.0 Predictive Maintenance (PdM 4.0) architecture in the broadcasting chain is one of the taxonomy challenges for deploying Industry 4.0 frameworks. This paper proposes a novel PdM framework based on advanced Reference Architecture Model Industry 4.0 (RAMI 4.0) to reduce operation and maintenance costs. This framework includes real-time production monitoring, business processes, and integration based on Design Science Research (DSR) to generate an innovative Business Process Model and Notation (BPMN) meta-model. The addressed model visualizes sub-processes based on experts' and stakeholders' knowledge to reduce the cost of maintenance of audiovisual services including satellite TV, cable TV, and live audio and video broadcast services. Based on the recommendation and the concept of Industry 4.0, the proposed framework tolerates the predictable failures and further concerns in similar related industries. Some empirical experiments have been conducted by using the Islamic Republic of Iran Broadcasting’s (IRIB) high-power station (located near the capital city of Iran, Tehran) to evaluate the functionality and efficiency of the proposed predictive maintenance framework. Practical outcomes demonstrate that interval times between data collection should be increased in audio and video broadcasting predictive maintenance because of the limitation of the internal processing performance of equipment. The framework also indicates the role of the Frequency Modulation (FM) transmitters’ data clearance to reduce the instability and untrustworthy data during data mining. The proposed DSR method endorses using a customized RAMI 4.0 meta-model framework to adapt distributed broadcasting and communication with PdM 4.0, which increases the stability as well as decreasing maintenance costs of the broadcasting chain in comparison to state-of-the-art methodologies. Furthermore, it is shown that the proposed framework outperforms the best-evaluated methods in terms of acceptance.     

A function-oriented biologically analogical approach for constructing the design concept of smart product in Industry 4.0

The development of the Industry 4.0 paradigm and the advancement of information technology have aroused new consumer requirements for smart products that are capable of context awareness and autonomous control. Nature holds huge potential for inspiring innovative design concepts that can meet the ever-growing need for smart products since biology perceive and interact with their living environment for survival. However, to date, very few studies have explored the application of natural wisdom in building innovative design concepts for smart products. This paper proposes a function-oriented design approach for smart products, by analogizing to biological prototypes. To do so, a unified functional representation, based on the Function–behavior–structure (FBS) ontology, is proposed to abstract biological prototypes, followed by a fuzzy triangular numbers-based algorithm designed to locate appropriate biological prototypes as analogical sources for smart product development. Moreover, functional innovative strategies and a hybrid design process are formulated to develop design concepts of smart products, by integrating several existing engineering design methods. Finally, an illustrative design case of a smart natural resource collecting system is used to demonstrate the workability of the proposed method.     

Innovation in the Agri‐Food sector: Exploiting opportunities for Industry 4.0

Agri‐Food producers have a responsibility to provide safe, secure and sustainable food in a world characterized by disruption and increasing intolerance of waste along supply chains. As such, it is critical that they adopt new technologies to ensure efficient and effective management of their responsibility. While Industry 4.0 (I4.0) technologies can underpin process innovation opportunities, there is a gap in research‐based understanding of how they influence innovation practice and outcomes in Agri‐Food. In this paper, we investigate how I4.0, as a set of enabling technologies, influences core process innovation practice and product innovation outcomes in Agri‐Food firms. We present case studies of two Spanish firms processing fresh food products, competing in two important subsectors of the industry, meat and fruit and vegetables. We used secondary material and semi‐structured interviews as data sources. The findings describe how, in the two cases, I4.0 has enabled responses to new customers requirements through process innovations resulting in enhanced functionality, aesthetics and meaning of the delivered products. Our paper contributes a framework identifying for researchers and managers how I4.0 technologies act as enablers of the core innovation processes and competitive outcomes.     

Supporting disassembly processes through simulation tools: A systematic literature review with a focus on printed circuit boards

Several strategies have been detected in the extant literature to understand how Circular Economy (CE) can be pursued. Considering all the End-of-Life (EoL) management practices detected, disassembly processes have been identified as strategic. However, only scattered attempts have explored how digital technologies (specifically, simulation) can support the CE adoption, by focusing on disassembly processes. This research detects, through a systematic literature review, how so far simulation approaches have been proposed and applied in the extant literature to foster the disassembly process with a focus on Printed Circuit Boards (PCBs). At this purpose, the main roles played by simulation to ease the disassembly process, also through the support of Industry 4.0 (I4.0) technologies, have been detected. Based on the results obtained, two roles of simulation to support the disassembly process (Sequence planning and process optimization and Training) seem the most interesting from the twofold CE/I4.0 perspective, combining up to date technologies with traditional simulation approaches. Discussed in a deeper and sector-independent way, results provide directions about the lifecycle phases to be explored through simulations, the technologies to be involved, and both the final purpose and the type of simulation approach to be adopted. Finally, the gaps needing for further contributions, raised from the adoption of a Digitized Disassembly, are listed, and the main technologies so far employed to cope with them, through a Virtual/Augmented Disassembly-oriented Simulation perspective, have also been detected and provided as a guide for those who want to approach the hybrid simulation/disassembly research context.     

A review of essential standards and patent landscapes for the Internet of Things: A key enabler for Industry 4.0

This paper is a formal overview of standards and patents for Internet of Things (IoT) as a key enabler for the next generation advanced manufacturing, referred as Industry 4.0 (I 4.0). IoT at the fundamental level is a means of connecting physical objects to the Internet as a ubiquitous network that enables objects to collect and exchange information. The manufacturing industry is seeking versatile manufacturing service provisions to overcome shortened product life cycles, increased labor costs, and fluctuating customer needs for competitive marketplaces. This paper depicts a systematic approach to review IoT technology standards and patents. The thorough analysis and overview include the essential standard landscape and the patent landscape based on the governing standards organizations for America, Europe and China where most global manufacturing bases are located. The literature of emerging IoT standards from the International Organization for Standardization (ISO), the International Electrotechnical Commission (IEC) and the Guobiao standards (GB), and global patents issued in US, Europe, China and World Intellectual Property Organization (WIPO) are systematically presented in this study.     

IoT-enabled smart appliances under industry 4.0: A case study

Manufacturers expect the extra value of Industry 4.0 as the world is experiencing digital transformation. Studies have proved the potential of the Internet of Things (IoT) for reducing cost, improving efficiency, quality, and achieving data-oriented predictive maintenance services. Collecting a wide range of real-time data from products and the environment requires smart sensors, reliable communications, and seamless integration. IoT, as a critical Industry 4.0 enabler emerges smart home appliances for higher customer satisfaction, energy efficiency, personalisation, and advanced Big data analytics. However, established factories with limited resources are facing challenges to change the longstanding production lines and meet customer’s requirements. This study aims to fulfil the gaps by transforming conventional home appliances to IoT-enabled smart systems with the ability to integrate into a smart home system. An industry-led case study demonstrates how to turn conventional appliances to smart products and systems (SPS) by utilising the state-of-the-art Industry 4.0 technologies.     

Modeling and simulation of complex manufacturing phenomena using sensor signals from the perspective of Industry 4.0

This article presents a methodology defined as semantic modeling to create computable virtual abstractions of complex manufacturing phenomena denoted as phenomena twins from the perspective of the fourth industrial revolution (also known as Smart Manufacturing, Connected Factory, Industry 4.0, and so forth). The twins are created such that they become friendly to both sensor signals and new-generation web technology (i.e., the semantic web). The efficacy of the proposed modeling approach is demonstrated by creating a phenomenon twin of cutting force (a highly complex and stochastic phenomenon associated with all material removal processes) and also by representing it using the semantic web. The relevant epistemological and systemological issues (e.g., those of meta-models, ontology, classification/trustworthiness/provenance of knowledge associated with the webized phenomenon twin) are also discussed. This article will help developers of embedded (e.g., cyber-physical) systems needed for functionalizing Industry 4.0.     

Digital Twin as a Service (DTaaS) in Industry 4.0: An Architecture Reference Model

Recent findings have shown that Digital Twin served multiple constituencies. However, the dilemma between the scope and scale needs a sophisticated reference architecture, a right set of technologies, and a suitable business model. Most studies in the Digital Twin field have only focused on manufacturing and proposed explicit frameworks and architecture, which faced challenges to support different integration levels through an agile process. Besides, no known empirical research has focused on exploring relationships between Digital Twin and mass individualization. Therefore, the principal objective of this study was to identify suitable Industry 4.0 technologies and a holistic reference architecture model to accomplish the most challenging Digital Twin enabled applications. In this study, a Digital Twin reference architecture was developed and applied in an industrial case. Also, Digital Twin as a Service (DTaaS) paradigm utilized for the digital transformation of unique wetlands with considerable advantages, including smart scheduled maintenance, real-time monitoring, remote controlling, and predicting functionalities. The findings indicate that there is a significant relationship between Digital Twin capabilities as a service and mass individualization.     

Developing technological capabilities for Industry 4.0 adoption: An analysis of the role of inbound open innovation in small and medium-sized enterprises

To keep up with rapid technological change, firms are pushed to acquire new competencies and resources, often leveraging the external networks in which they are involved. The paper examines how firms' engagement in inbound open innovation (OI) enables the adoption of Industry 4.0 (I4.0) technologies in small and medium-sized enterprises (SMEs) through the deployment of technological capabilities. We combine the OI and dynamic capabilities frameworks to assess how the absorption of knowledge from different actors impacts the necessary technological capabilities for adopting I4.0 technologies. The capabilities are categorized in technological sensing, seizing and reconfiguring. The study is based on in-depth case studies of two selected SMEs from the footwear industry. The cases show that engaging in external collaborations, particularly with universities, pushes SMEs to renew the bundle of competencies underlying their technological capabilities. However, this effect is influenced by the OI modalities adopted by both companies. While in Company A OI takes place through a broader array of formal and informal linkages that contribute to the exploration of distant knowledge bases and the experimentation of more diverse technologies, such as the Internet of Things, Company B relies on informal networking concentrated in its own field of specialization for the adoption of manufacturing-specific I4.0 solutions, such as automated robots and 3D printing.     

Knowledge-Based Virtual Modeling and Simulation of Manufacturing Processes for Industry 4.0

Abstract

Industry 4.0 aims at providing a digital representation of a production landscape, but the challenges in building, maintaining, optimizing, and evolving digital models in inter-organizational production chains have not been identified yet in a systematic manner. In this paper, various Industry 4.0 research and technical challenges are addressed, and their present scenario is discussed. Moreover, in this article, the novel concept of developing experience-based virtual models of engineering entities, process, and the factory is presented. These models of production units, processes, and procedures are accomplished by virtual engineering object (VEO), virtual engineering process (VEP), and virtual engineering factory (VEF), using the knowledge representation technique of Decisional DNA. This blend of the virtual and physical domains permits monitoring of systems and analysis of data to foresee problems before they occur, develop new opportunities, prevent downtime, and even plan for the future by using simulations. Furthermore, the proposed virtual model concept not only has the capability of Query Processing and Data Integration for Industrial Data but also real-time visualization of data stream processing.     

A cost benefit analysis for industry 4.0 in a job shop environment using a mixed integer linear programming model

As the manufacturing industry is approaching implementation of the 4th industrial revolution, changes will be required in terms of scheduling, production planning and control as well as cost-accounting departments. Industry 4.0 promotes decentralized production and hence, cost models are required to capture costs of products and jobs within the production network considering the utilized manufacturing system paradigm A new mathematical cost model is proposed for assessing the cost-benefit analysis of introducing Industry 4.0 elements to the manufacturing facility, specifically, integrating and connecting external suppliers as strategic partners and establishing an infrastructure for communicating information between the manufacturing company and its strategic suppliers. The mathematical model takes into consideration the bi-directional relationship between hourly rates and total hours assigned to workcentres/activities in a certain production period. A case study, from a multinational machine builder, is developed and solved using the proposed model. Results suggest that though an additional cost is required to establish infrastructure to connect suppliers, the responsiveness and agility achieved resulting from uncertainty outweighs the additional cost.     

Real Time Automation and Ratio Control Using PLC & SCADA in Industry 4.0

Industrial Control Systems (ICS) and SCADA (Supervisory Control and Data Acquisition) systems play a critical role in the management and regulation of critical infrastructure. SCADA systems brings us closer to the real-time application world. All process and equipment control capability is typically provided by a Distributed Control System (DCS) in industries such as power stations, agricultural systems, chemical and water treatment plants. Instead of control through DCS, this paper proposes a SCADA and PLC (Programmable Logic Controller) system to control the ratio control division and the assembly line division inside the chemical plant. A specific design and implementation method for development of SCADA/PLC based real time ratio control and automated assembly line system in a chemical plant is introduced. The assembly line division is further divided into sorting stage, filling stage and the auxiliary stage, which includes the capping unit, labelling unit and then the storage. In the ratio control division, we have defined the levels inside the mixer and ratio of the raw materials through human machine interface (HMI) panel. The ratio of raw materials is kept constant on the basis of flow rates of wild stream and manipulated stream. There is a flexibility in defining new levels and the ratios of the raw materials inside the mixer. But here we taken the predefined levels (low, medium, high) and ratios (3:4, 2:1, 2:5). Control valves are used for regulating the flow of the compositions. In the assembly line division, the containers are sorted on the basis of size and type of material used i.e., big sized metallic containers and small sized non-metallic containers by inductive and capacitive proximity sensors. All the processes are facilitated with laser beam type or reflective type sensors on the conveyor system. Building a highly stable and dependable PLC/SCADA system instead of Distributed Control System is required to achieve automatic management and control of chemical industry processes to reduce waste manpower and physical resources, as well as to improve worker safety.     

Mass customized/personalized manufacturing in Industry 4.0 and blockchain: Research challenges,main problems,and the design of an information architecture

Mass customized and mass personalized production has become facilitated by the fourth industrial revolution. The resulting industrial environments require the development of information systems able to take the specifications of customers and convey them to the production system in such a way as to contribute to the coordination of all the stakeholders and activities required to fulfill the orders of the customers. This is beyond the capabilities of traditional systems based on MRP and ERP, since the information should be managed in a flexible and decentralized way to exploit the Smart Manufacturing facilities of Industry 4.0. Blockchain, instead, is a technology that provides those features constituting a sound information supporting basis for mass customized/personalized production. Consequently, we explore the potential of blockchain as an information technology able to support industries that base their business models on mass customized/personalized production processes. This survey allows us to identify important challenges for further developments, highlighting three issues in the production setting: (i) to deepen the interoperability of systems, (ii) to generate more implementations, and (iii) to develop efficient consensus protocols. As a response to these insights we provide a conceptual design of how blockchain contributes to managing efficiently mass customized production systems. In our design the information of customer specifications can be fused with data from the production process to generate a plan to fulfill the demand. This design arises as a solution approach to three stated problem, which are faced by mass customized production systems.