Industry 4.0 integration with socio-technical systems theory: A systematic review and proposed theoretical model

Industry 4.0 promises the fourth industrial revolution by integration of cyber and physical worlds through technology. Industry 4.0 implementation will result in human interaction with technical system in a specialised manner. Therefore, Industry 4.0 will also be a socio (human related) and technical (nonhuman related) system in pursuit of a common goal. The purpose of this study is to suggest a mechanism to include Socio-Technical Systems Theory perspective while designing architecture for integration while implementing Industry 4.0. Building on the previous literatures on Socio-Technical Systems Theory and Industry 4.0, the article proposes bringing the two approaches together and presents a framework for integration mechanism. Successful implementation of Industry 4.0 warrants vertical, horizontal and end-to-end integration. This study suggests a design mechanism for three types of integration mechanism in Industry 4.0 by considering the socio-technical systems impact on people, infrastructure, technology, processes, culture and goals. Further, the integration is also suggested for analysis on the impact of stakeholders, economic situation and regulatory frameworks around which the operating organizations are operating. This is the first paper to propose the consideration of Socio-Technical Systems theory while designing the horizontal, vertical and end-to-end integration for sustainable implementation of Industry 4.0.     

FogQSYM: An Industry 4.0 Analytical Model for Fog Applications

Industry 4.0 refers to the fourth evolution of technology development, which strives to connect people to various industries in terms of achieving their expected outcomes efficiently. However, resource management in an Industry 4.0 network is very complex and challenging. To manage and provide suitable resources to each service, we propose a FogQSYM (Fog–-Queuing system) model; it is an analytical model for Fog Applications that helps divide the application into several layers, then enables the sharing of the resources in an effective way according to the availability of memory, bandwidth, and network services. It follows the Markovian queuing model that helps identify the service rates of the devices, the availability of the system, and the number of jobs in the Industry 4.0 systems, which helps applications process data with a reasonable response time. An experiment is conducted using a Cloud Analyst simulator with multiple segments of datacenters in a fog application, which shows that the model helps efficiently provide the arrival resources to the appropriate services with a low response time. After implementing the proposed model with different sizes of fog services in Industry 4.0 applications, FogQSYM provides a lower response time than the existing optimized response time model. It should also be noted that the average response time increases when the arrival rate increases.     

Implementation of Industry 4.0 and lean production in Brazilian manufacturing companies

The adoption of Industry 4.0 technologies has been deemed as a strategy to increase product quality and make manufacturing processes more efficient. However, the way that these technologies are integrated into existing production systems and which processes they can support is still under investigation. Thus, this paper aims to examine the relationship between lean production (LP) practices and the implementation of Industry 4.0 in Brazilian manufacturing companies. To achieve that we use data from a survey carried out with 110 companies of different sizes and sectors, at different stages of LP implementation. Data collected were analysed by means of multivariate analysis. Our findings indicate that LP practices are positively associated with Industry 4.0 technologies and their concurrent implementation leads to larger performance improvements. Further, the contextual variables investigated do matter to this association, although not all aspects matter to the same extent and effect.     

The relevance of Industry 4.0 and its relationship with moving manufacturing out,back and staying at home

In view of the fact that Industry 4.0 is becoming increasingly essential, the implementation of Industry 4.0 technologies is believed to be an essential strategic component in further increasing the efficiency of manufacturing processes and in determining decisions concerning globalisation strategies. Thus, this paper provides an empirical analysis of the essential constructs of Industry 4.0, and drivers and barriers for Industry 4.0. The paper is based on 270 valid answers to a questionnaire-survey distributed among Danish manufacturers. Regression analyses were used to test the proposed hypotheses. The results of the analyses reveal that the identified drivers and barriers for Industry 4.0 have a positive impact on the perceived relevance of Industry 4.0 among companies. Furthermore, the analyses show that the perceived relevance of Industry 4.0 among companies has a positive impact on companies that have moved manufacturing back and on companies that have moved manufacturing out and back. Conversely, the perceived relevance of Industry 4.0 among companies has a negative impact on companies that have remained domestic. The perceived relevance of Industry 4.0 has no impact on companies that have moved manufacturing out. This research, in general, offers to both researchers and practitioners an increased consciousness concerning the relevant drivers and barriers for Industry 4.0 in decision processes about where to locate manufacturing.     

Scientific mapping to identify competencies required by industry 4.0

The objective of this study was to identify what competencies are identified in the literature as necessary for Industry 4.0 by conducting a survey of the literature and a scientific mapping of the evolution of the issues related to the qualification of professionals for Industry 4.0 and possible paths for research and education. A search was conducted on the Scopus, Web of Science and Science Direct databases for the interval from 2010 to 2018. This systematic review revealed topics and authors currently specialized in the field and allowed mapping the field of study. The identification of journals and keywords useful in future studies was also an object of this study. SciMAT software was used for the systematic literature review. The results are highlighted by the set of competencies (knowledge and skills) that must be developed in professional education to accompany the new industrial revolution, as well as the importance of integrating efforts by companies, governments and universities. These efforts should focus on creating “learning factories”, which are understood to be environments that provide practical experiences to these professionals, preparing them in the best way possible for the requirements of Industry 4.0. This conceptual map showed that the main competencies needed include skills: (leadership, strategic vision of knowledge, self-organization, giving and receiving feedback, pro-activity, creativity, problem solving, interdisciplinarity, teamwork, collaborative work, initiative, communication, innovation, adaptability, flexibility and self-management) and knowledge of contemporary fields (information and communication technology, algorithms, automation, software development and security, data analysis, general systems theory and sustainable development theory).     

Observed use of automatic seat belts in 1987 cars

Usage of the automatic belt systems supplied by six large-volume automobile manufacturers to meet the federal requirements for automatic restraints were observed in suburban Washington, D.C., Chicago, Los Angeles, and Philadelphia. The different belt systems studied were: Ford and Toyota (motorized, nondetachable automatic shoulder belt), Nissan (motorized, detachable shoulder belt), VW and Chrysler (nonmotorized, detachable shoulder belt), and GM (nonmotorized detachable lap and shoulder belt). Use of automatic belts was significantly greater than manual belt use in otherwise comparable late-model cars for all manufacturers except Chrysler; in Chrysler cars, automatic belt use was significantly lower than manual belt use. The automatic shoulder belts provided by Ford, Nissan, Toyota, and VW increased use rates to about 90%. Because use rates were lower in Ford cars with manual belts, their increase was greater. GM cars had the smallest increase in use rates; however, lap belt use was highest in GM cars. The other manufacturers supply knee bolsters to supplement shoulder belt protection; all--except VW--also provide manual lap belts, which were used by about half of those who used the automatic shoulder belt. The results indicate that some manufacturers have been more successful than others in providing automatic belt systems that result in high use that, in turn, will mean fewer deaths and injuries in those cars.     

Modelling and quantification of industry 4.0 manufacturing complexity based on information theory: a robotics case study

The new industrial revolution called Industry 4.0 imposes new challenges to the research community. One of the main issues in Industry 4.0 is the management of the huge amount of information exchanged among its different integrated systems. The present work demonstrates how the traditional manufacturing system is transformed to the Industry 4.0 manufacturing system and proposes a modelling and quantification approach, which includes metrics from the Information Theory estimating the complexity and the capacity of the Industry 4.0, from the perspective of the communication among the systems. The application impact of the proposed Industry 4.0 system and the comparison of these metrics before and after shifting to Industry 4.0 is also analysed and validated in a case study from the Robotics Industry.     

Industry 4.0 and resilience in the supply chain: a driver of capability enhancement or capability loss?

The purpose of this research is to develop a better understanding of smart systems and autonomous processes of the Industry 4.0 era. Does the implementation of Industry 4.0 processes and systems expose firms to higher levels of risk in the supply chain through capability loss or does Industry 4.0 spur capability enhancement and thereby increase supply chain resilience? Industry 4.0 is centred on the idea that certain tasks and decisions can be automated through smart systems and autonomous processes. However, is there a risk of losing critical capabilities and the ability to be flexible, agile and resilient to unexpected disruptions in the supply chain? In order to address these questions, this research presents results from semi-structured interviews across multiple industries to provide findings on firms’ uses of smart systems and capability development associated with these systems. Results from this exploratory study may be classified into two primary insights. First, although Industry 4.0 systems are new and, in many cases untested, firms are eager regarding the potential of smart systems to positively impact firm performance and to leverage Industry 4.0 processes for a competitive supply chain advantage. Second, companies did not claim any human capability loss associated with Industry 4.0. In fact, these smart systems may lead to increased supply chain resilience because of capability enhancement and new skill development.     

The industrial management of SMEs in the era of Industry 4.0

Industry 4.0 provides new paradigms for the industrial management of SMEs. Supported by a growing number of new technologies, this concept appears more flexible and less expensive than traditional enterprise information systems such as ERP and MES. However, SMEs find themselves ill-equipped to face these new possibilities regarding their production planning and control functions. This paper presents a literature review of existing applied research covering different Industry 4.0 issues with regard to SMEs. Papers are classified according to a new framework which allows identification of the targeted performance objectives, the required managerial capacities and the selected group of technologies for each selected case. Our results show that SMEs do not exploit all the resources for implementing Industry 4.0 and often limit themselves to the adoption of Cloud Computing and the Internet of Things. Likewise, SMEs seem to have adopted Industry 4.0 concepts only for monitoring industrial processes and there is still absence of real applications in the field of production planning. Finally, our literature review shows that reported Industry 4.0 projects in SMEs remained cost-driven initiatives and there in still no evidence of real business model transformation at this time.     

Industry 4.0: state of the art and future trends

Rapid advances in industrialisation and informatisation methods have spurred tremendous progress in developing the next generation of manufacturing technology. Today, we are on the cusp of the Fourth Industrial Revolution. In 2013, amongst one of 10 ‘Future Projects’ identified by the German government as part of its High-Tech Strategy 2020 Action Plan, the Industry 4.0 project is considered to be a major endeavour for Germany to establish itself as a leader of integrated industry. In 2014, China’s State Council unveiled their ten-year national plan, Made-in-China 2025, which was designed to transform China from the world’s workshop into a world manufacturing power. Made-in-China 2025 is an initiative to comprehensively upgrade China’s industry including the manufacturing sector. In Industry 4.0 and Made-in-China 2025, many applications require a combination of recently emerging new technologies, which is giving rise to the emergence of Industry 4.0. Such technologies originate from different disciplines including cyber-physical Systems, IoT, cloud computing, Industrial Integration, Enterprise Architecture, SOA, Business Process Management, Industrial Information Integration and others. At this present moment, the lack of powerful tools still poses a major obstacle for exploiting the full potential of Industry 4.0. In particular, formal methods and systems methods are crucial for realising Industry 4.0, which poses unique challenges. In this paper, we briefly survey the state of the art in the area of Industry 4.0 as it relates to industries.     

Die häufigsten Fehler beim Einsatz von Vakuumpumpen und deren Vermeidung

How to avoid operating errors The rising number of vacuum pump applications require, that the vacuum pump manufacturers develop and offer more and more application dedicated products. To make sure the pumps fulfil the application requirements with regards to performance and reliability, certain operational measures to be followed. From the pump manufacturers standpoint this article shall emphasize helpful tips regarding selection, operation, accessories, monitoring and preventive maintenance for users and system manufacturers for the most common vacuum pumps.     

A method for identifying customer orientations and requirements for product–service systems design

For manufacturers, developing product–service systems (PSSs) is getting more important because of the trends of servitisation and creating social value. A PSS is a social system where multiple actors mutually provide products and services. A PSS design, therefore, must take into account various actors as customers. However, existing methods provide an insufficient solution as to how various customers should be handled in an analysis to identify and accommodate various customer preferences and requirements. To tackle this issue, this article proposes a new method of identifying customers’ orientations and requirements for PSS design. The proposed method employs a combination of topic analysis, persona and scenario approaches. The effectiveness of the method is demonstrated with its application to an urban development case. Through the demonstration, its practical benefits are concluded as follows: consistent and logical results of requirement analysis and insights into a new market for manufacturers.     

Big data and machine learning: A roadmap towards smart plants

Industry 4.0 aims to transform chemical and biochemical processes into intelligent systems via the integration of digital components with the actual physical units involved. This process can be thought of as addition of a central nervous system with a sensing and control monitoring of components and regulating the performance of the individual physical assets (processes, units, etc.) involved. Established technologies central to the digital integrating components are smart sensing, mobile communication, Internet of Things, modelling and simulation, advanced data processing, storage and analysis, advanced process control, artificial intelligence and machine learning, cloud computing, and virtual and augmented reality. An essential element to this transformation is the exploitation of large amounts of historical process data and large volumes of data generated in real-time by smart sensors widely used in industry. Exploitation of the information contained in these data requires the use of advanced machine learning and artificial intelligence technologies integrated with more traditional modelling techniques. The purpose of this paper is twofold: a) to present the state-of-the-art of the aforementioned technologies, and b) to present a strategic plan for their integration toward the goal of an autonomous smart plant capable of self-adaption and self-regulation for short- and long-term production management.     

HFGZ22 型回转式负压灌装机的研制

目的针对当前自动灌装技术发展中提出的大批量灌装要求,研制一种HFGZ22型回转式负压灌装机。方法比较分析各种灌装方法,采用抽真空与液体灌装同时进行的方式,并利用气压平衡原理控制灌装量;根据目标液体特性,采用机械式托瓶方式实现瓶口的自动密封。结果设备应用表明,该灌装机综合性能优、可靠性高、适应性强、运行平稳,且无液体滴漏等现象,达到预期设计目标。结论该型号灌装机可广泛应用于中小型食品饮料生产企业。     

A dynamic model and an algorithm for short-term supply chain scheduling in the smart factory industry 4.0

Smart factories Industry 4.0 on the basis of collaborative cyber-physical systems represents a future form of industrial networks. Supply chains in such networks have dynamic structures which evolve over time. In these settings, short-term supply chain scheduling in smart factories Industry 4.0 is challenged by temporal machine structures, different processing speed at parallel machines and dynamic job arrivals. In this study, for the first time, a dynamic model and algorithm for short-term supply chain scheduling in smart factories Industry 4.0 is presented. The peculiarity of the considered problem is the simultaneous consideration of both machine structure selection and job assignments. The scheduling approach is based on a dynamic non-stationary interpretation of the execution of the jobs and a temporal decomposition of the scheduling problem. The algorithmic realisation is based on a modified form of the continuous maximum principle blended with mathematical optimisation. A detailed theoretical analysis of the temporal decomposition and computational complexity is performed. The optimality conditions as well as the structural properties of the model and the algorithm are investigated. Advantages and limitations of the proposed approach are discussed.     

Improved Systems Understanding by Similarities and Analogies

ABSTRACT

A set of definitions of systems engineering concepts is the point of departure of this article. Those definitions are generic and cover the system and its life cycle, the systems engineering discipline, and the systems engineering process. A systems engineer must be able to analyze and understand systems first on a conceptual level independent of technology, that is, a technology-free functional analysis. More detailed knowledge and deeper insight into a concrete technology are required later. The systems engineer must be able to move from one system project to another, sometimes with entirely different technologies and requirements. This article points to a need for greater flexibility and easier adaptability on the part of the systems engineer. This need implies that the knowledge base and professional toolbox for the systems engineer must meet this requirement also. A way this requirement can be met is by system similarity and the principle of analogy between functional characteristics of systems.     

真空自动控制基础

介绍了真空自动控制的基本概念、名词术语、真空自动控制的基本规律，以及真空自动控制系统的构成、分类和要求。     

新型陶瓷快速成型装置数控系统的研究

基于GT400运动控制器的开放式体系结构的数控系统软硬件平台及其关键技术,研究陶瓷零件快速成型设备数控系统对于缩短陶瓷零件的制造周期以及提高企业的生产效率所具有的重要意义.阐述了陶瓷零件快速成型机的新工艺方法和特点,对新型陶瓷零件快速成型机机械系统及其控制要求作了详细分析,着重介绍了陶瓷零件快速成型机控制系统的硬件设计及自顶向下的软件设计.利用Visual C++6.0开发工具和GT系列运动控制器自带的DLL动态链接库开发了操作方便、运行稳定、加工精度高的开放式陶瓷快速成型装置数控系统.控制系统能够很好地满足系统开放性的要求及产品自动化生产的要求,提高了经济效益.     

An empirical study for smart production for TFT-LCD to empower Industry 3.5

Abstract

With increasing technological advancements, manufacturing intelligence has become a crucial issue for maintaining competitive advantages. Industry 4.0, proposed by Germany, is one of the large-scale projects to achieve manufacturing intelligence and smart production. Others include the Advanced Manufacturing Partnership 2.0 (AMP2.0) from the United States, Industry 4.1J of Japan and Made in China 2025. On the other hand, most of the emerging countries may not be ready for the migration of Industry 4.0 directly since their industrial infrastructures are different with the leading countries. This study aims to propose Industry 3.5 as a hybrid strategy between existing Industry 3.0 and to-be Industry 4.0, in which digital decision-making, big data analytics, and manufacturing intelligence are integrated to empower smart production with disruptive innovations that can be realized in existing industrial infrastructure. To estimate the validity of the proposed Industry 3.5, an empirical study was conducted in a thin film transistor liquid crystal display (TFT-LCD) manufacturing factory in Taiwan. A smart daily planning and scheduling (DPS) system is developed to enhance manufacturing intelligence for smart production without a fully automation facility as the Cyber-Physical System proposed in Industry 4.0. This study concludes with discussions of development directions for industrial revolution.     

An empirical evaluation of industry 4.0 applications of companies in Turkey: The case of a developing country

The main purpose of this paper is to investigate Industry 4.0 applications in companies of Turkey, a developing country. It also aims to determine how the following factors affect the level of Industry 4.0 applications: technological level of products manufactured, the presence of an R&D department, and the size of the company. A specially-designed questionnaire was used in the survey. According to the results of our research, it can be stated that companies that produce highly technological products are more likely to develop Industry 4.0 applications and to implement Industry 4.0 technologies. If companies of developing countries expense more for R&D, it is expected that their readiness for Industry 4.0 transformation will also be higher. According to our survey, productivity is the main benefit expected by Industry 4.0 applications and lack of technical skills and expertise is one of the most important challenge of Industry 4.0 transformation of companies in Turkey.