Human factors in production and logistics systems of the future

The way humans work in production and logistics systems is changing. The evolution of technologies, Industry 4.0 applications, and societal changes, such as ageing workforces, are transforming operations processes. This transformation is still a “black-box” for many companies, and there are calls for new management approaches that can help to successfully overcome the future challenges in production and logistics.While Industry 4.0 emerges, companies have started to use advanced control tools enabled by real-time monitoring systems that allow the development of more accurate planning models that enable proactive managerial decision-making. Although we observe an increasing trend in automating human work in almost every industry, human workers are still playing a central role in many production and logistics systems. Many of these planning models developed for managerial decision support, however, do not consider human factors and their impact on system or employee performance, leading to inaccurate planning results and decisions, underperforming systems, and increased health hazards for employees.This paper summarizes the vision, challenges and opportunities in this research field, based on the experience of the authors, members of the Working Group 7 (WG7) “Human factors and ergonomics in industrial and logistic system design and management” of the IFAC Technical Committee (TC) 5.2 “Manufacturing Modelling for Management and Control". We also discuss the development of this research stream in light of the contributions presented in invited sessions at related IFAC conferences over the last five years. The TC 5.2 framework is adapted to include a human-centered perspective. Based on this discussion, a research agenda is developed that highlights the potential benefits and future requirements for academia and society in this emerging research field. Promising directions for future research on human factors in production and logistics systems include the consideration of diversity of human workers and an in-depth integration of Industry 4.0 technologies in operations processes to support the development of smart, sustainable, human-centered systems.     

Ubiquitous manufacturing: Current practices,challenges, and opportunities

Ubiquitous manufacturing (UM) features a “design anywhere, make anywhere, sell anywhere, and at any time” paradigm that grants factories an unlimited production capacity and permanent manufacturing service availability. However, the research and applications of UM have been limited thus far to in-factory operations or logistics. For this reason, this study reviews the current practices of UM, discusses the challenges faced by researchers and practitioners, and determines potential opportunities for UM in the near future. Finally, we conclude that the success of UM depends on the quality of the manufacturing services deployed, and that UM is a realizable target for Industry 4.0.     

Proposal-Based Graph Attention Networks for Workflow Detection

Neural Processing Letters - In the process of “Industry 4.0”, video analysis plays a vital role in a variety of industrial applications. Video-based action detection has obtained...     

Production logistics digital twins: Research profiling,application, challenges and opportunities

In the era of Industry 4.0, Production Logistic Digital Twins (PLDTs) have garnered remarkable attention from both academic and industrial communities. This is evident from the growing number of research publications on PLDTs in international scientific journals and conferences. However, given the diversity and complexity of production logistics activities, there is a pressing need for systematic literature review to chart past research and identify potential directions for future endeavors. Therefore, this study primarily focuses on the application of Digital Twins (DTs) in Production Logistics (PL). Firstly, an analysis of PLDTs research profiling is carried out based on general trends, keywords, application scenarios, and basic functions. Secondly, the functional characteristics of PLDTs are examined while summarizing their advantages and limitations across various application scenarios such as transportation, packaging, warehousing, material distribution, and information processing. And the roles played by smart technologies such as Internet of Things (IoT) in PLDTs system are discussed. Finally, possible challenges and future directions of PLDTs in industrial application are presented, accompanied by appropriate classification and extensive recommendations.     

Applications of virtual reality in maintenance during the industrial product lifecycle: A systematic review

As a state-of-the-art computer technology, virtual reality (VR) is considered to play an important role in helping manufacturing companies stay competitive in the international market. However, despite the achievements made in the field of VR, it is still an emerging technology that lacks deeper exploration and development in industrial application scenarios, especially in the coming fourth industrial revolution (Industry 4.0). This paper aims to systematically investigate the applications of VR in industrial maintenance to discover evidence of its values, limitations, and future directions so that VR can be guided to better serve manufacturing enterprises in remaining competitive in the coming Industry 4.0. A systematic literature review (SLR) methodology is adopted to review primary studies on this topic, by which 86 studies are ultimately included. The results show that VR has proved its value in benefiting maintenance issues through the product lifecycle. However, VR is still not an indispensable element for the lifecycle management of products regarding maintenance-related issues. Several key findings are concluded based on the analysis of the 86 studies. This review is valuable for researchers who are interested in the application of VR technology in maintainability design, maintenance training or maintenance task assistance.     

A survey on control theory applications to operational systems,supply chain management,and Industry 4.0

Modern production and logistics systems, supply chains, and Industry 4.0 networks are challenged by increased uncertainty and risks, multiple feedback cycles, and dynamics. Control theory is an interesting research avenue which contributes to further insights concerning the management of the given challenges in operations and supply chain management. In this paper, the applicability of control theory to engineering and management problems in supply chain operations is investigated. Our analysis bridges the fundamentals of control and systems theory to supply chain and operations management. This study extends our previous survey in the Annual Reviews in Control (Ivanov et al. 2012) by including new literature published in 2012–2018, identifying two new directions of control theory applications (i.e., ripple effect analysis in the supply chains and scheduling in Industry 4.0) and analysis towards the digital technology use in control theoretic models. It describes important issues and perspectives that delineate dynamics in supply chains, operations, and Industry 4.0 networks and identifies and systemizes different streams in the application of control theory to operations and supply chain management and engineering in the period from 1960–2018. It updates the existing applications and classifications, performs a critical analysis, and discusses further research avenues. Further development of interdisciplinary approaches to supply chain optimization is argued. An extended cooperation between control engineers and supply chain experts may have the potential to introduce more realism to dynamic planning and models, and improve performance in production and logistics systems, supply chains, and Industry 4.0 networks. Finally, we analyze the trends towards the intellectualization of control and its development towards supply chain control analytics.     

From industry 4.0 to society 4.0, there and back

The new industrial paradigm Industry 4.0, or smart industry, is at the core of contemporary debates. The public debate on Industry 4.0 typically offers two main perspectives: the technological one and the one about industrial policies. On the contrary, the discussion on the social and organizational effects of the new paradigm is still underdeveloped. The article specifically examines this aspect, and analyzes the change that workers are subject to, along with the work organization, smart digital factories. The study originates from an empirical survey conducted by the author together with a multidisciplinary research group between 2014 and 2015 in some of the largest Italian factories.In particular, the article analyzes the links between digital society, digital culture and Industry 4.0, focusing on the issue of people’s participation in the process of change, within a specific case study from the railway sector.Many elements of the Industry 4.0 paradigm are widespread outside the factory, in society; they are not only technological elements but also cultural. One of the key aspects of the analysis is the question of participation and the “person-centered” culture. The subject is addressed critically by presenting both the RE-personalization processes (from the centrality of the users–consumers in consumption practices to the centrality of the worker in the work paradigm 4.0) and the new processes of DE personalization caused by digital automation.     

Digitalisation and the regulation of work: theoretical issues and normative challenges

This paper presents an introductory overview of the main issues that the digitalisation of industrial enterprises known as Industry 4.0 raises for social sciences. First, it will show that this technological transition—which, however, is unfinished and is seen to be in continuity with the so-called “third industrial revolution”—cannot be interpreted with reference to a deterministic approach. It can be analysed more usefully as a range of decisions affecting the industrial policies of national states, the conception and design of machines, their adoption in production processes and finally their use by operators. Second, certain aspects of Industry 4.0 of special concern in terms of organisation of work processes will be analysed on various scales (from inter-company transactions to the specific tasks of individual workers). Finally, we will explain various hypotheses that social and economic research is developing with regard to the new technologies’ controversial effects on employment.     

How human factors affect operators' task evolution in Logistics 4.0

The spread of the Industry 4.0 paradigm introduced an increasing number of technological innovations into companies to improve logistics processes. During a transition to Logistics 4.0, it is necessary to consider all the issues that affect logistics, among which human factors (HF) are considered to be the most important. On the basis of the existing scientific literature, this article aimed to identify the relationships between 4.0 technologies implementation and HF concerning the evolution of human activities towards different hypothetical future scenarios (i.e., no changes, work replaced, or work assisted), analysing in detail the HF affected by 4.0 technologies. These relationships, which were summarised in a matrix, were also tested through a single longitudinal case study. The research showed that technology tends to replace logistics operators, not only for dangerous physical tasks but also for cognitive tasks that are stressful and repetitive. Moreover, for some tasks in which many different HF are involved, the evolution is towards operator assistance, rather than replacement.     

Challenges for the cyber-physical manufacturing enterprises of the future

This paper summarizes a vision of the challenges facing the so-called “Industry of the Future” as studied by the research community of the IFAC Coordinating Committee 5 on Manufacturing and Logistics Systems, which includes four Technical Committees (TC). Each TC brings its own vision and puts forward trends and issues important and relevant for future research. The analysis is performed on the enterprise-level topics with an interface too other relevant systems (e.g., supply chains). The vision developed might lead to the identification of new scientific control directions such as Industry 4.0 technology-enabled new production strategies that require highly customised supply network control, the creation of resilient enterprise to cope with risks, developments in management decision-support systems for the design, and scheduling and control of resilient and digital manufacturing networks, and collaborative control. Cobots, augmented reality and adaptable workstations are a few examples of how production and logistic systems are changing supporting the operator 4.0. Sustainable manufacturing techniques, such closed-loop supply chains, is another trend in this area. Due to increasing number of elements and systems, complex and heterogeneous enterprise systems need to be considered (e.g., for decision-making). These systems are heterogeneous and build by different stakeholders. To make use of these, an environment is needed that allows the integration of the systems forming a System-of-Systems (SoS). The changing environment requires models which adapt over time. Some of the adaptation is due to learning, other mechanisms include self-organisation by intelligent agents. In general, models and systems need to be modular and support modification and (self-)adaptation. An infrastructure is needed that supports loose coupling and evolving systems of systems. The vision of the overall contribution from the research community in manufacturing and logistics systems, over the next few years is to bring together researchers and practitioners presenting and discussing topics in modern manufacturing modelling, management and control in the emerging field of Industry 4.0-based resilient and innovative production SoS and supply networks.     

Segmentation preference and technostress: Integrators’ vs segmenters’ experience of technology-induced demands and related spill-over effects

Remote work is becoming the “new normal”, and more people are working in the home office due to the COVID-19 pandemic. Boundary management and the individual preferences to segment work and private life are a current topic of research as digital technologies have the potential to aggravate segmentation due to their invasive effect. In this context, we add to a current research stream on technostress, investigating technology-driven spill-over in a longitudinal study based on data assessed during the pandemic. The use of communication technologies leads to work-to-family stress due to the occurrence of techno-stressors interruptions, invasion, and overload. Differences between “segmenters” (people with a strong wish for separation) and “integrators” (who rather integrate life domains) were found. They experience techno-stressors differently in dependence on their technology use. Our paper offers interesting theoretical insights into boundary transcending effects of technology use. Recommendations for employers on how to shape the “new normal” are discussed.     

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.     

Analytical Network Process for logistics management: A case study in a small electronic appliances manufacturer

The purpose of this study is to present an application of Analytical Network Process (ANP) for determination of best logistics partnership strategy of a small electronic appliances manufacturer operating in Turkey. The model includes both qualitative and quantitative factors which have been determined by literature review and the expertise of the company managers. Three different logistics management alternatives, “In-house Logistics”, “Third Party Arrangements”, and “Strategic Alliance”, are evaluated by an ANP model. Pairwise comparisons have been obtained through a survey conducted with the company personnel and sector managers. The results provide a decision support for the company courting strategies for logistics management under the aspects of “Law and Regulations”, “Corporate Structure”, and “Economical Factors”; given in “Customer”, “Finance” and “Technology” Dimensions.     

A survey on decision-making based on system reliability in the context of Industry 4.0

The business world is continually changing. Dynamic environments, full of uncertainties, complexities, and ambiguities, demand faster and more confident decisions. To compete in this environment, Industry 4.0 emerges as an essential alternative. In this context, the reliability of manufacturing is an essential aspect for companies to make successful decisions. In the literature, several technologies associated with Industry 4.0 have been applied to improve the availability of equipment, including the Internet of Things (IoT), Cyber-Physical Systems (CPS), blockchain, and data mining. Nevertheless, there is still no survey study that seeks to show how reliability has collaborated to support decision-making in organizations, in the context of Industry 4.0. In general, most applications still focus on the productivity and health of individual equipment. However, in today's volatile and complex businesses, local decisions are no longer sufficient; it is necessary to analyze the organization entirely. Thus, being aware of the impacts that a local failure can impose on the entire company has significant weight in the decision-making process. In this context, this article presents a survey to identify how researches on systems reliability has contributed to and supported the development of decision-making in Industry 4.0. The main contribution of this article is to highlight how reliability can be used to support different types of strategic decisions in the context of Industry 4.0. Finally, it highlights the need for research associating management decisions with the technologies of Industry 4.0.     

A MORF-Vision Method for Strategic Creation of IoT Solution Opportunities

With the rise of Internet of Things (IoT), companies are now facing new challenges such as diverse consumer demands and shorter lifecycle of products and services. Even in big companies, they may have to “extract” new products every six months or less. Nonetheless, shorter lifecycle is never a waiver for poor user satisfaction. Common to the companies that survived such disruptive changes is that they emphasized the user experience (UX) as one of the most important elements of their strategy. This explains why most product innovation processes such as user-centered design or design thinking emphasize so much on “empathizing.” Developing a new product or service from scratch, however, is challenging especially when the underlying technology is new to people. The aim of this study is to develop a systematic process for creating opportunities from the UX perspective. This study suggests opportunity-creation process by adopting an “abductive” design thinking approach: (1) future envisioning and (2) opportunity identification and analysis. A new method called MORF-Vision (Morphological Future Envisioning) was developed to generate prospective scenarios that can be used in phase (2) to identify potential opportunities. An experiment showed that the MORF-Vision method is helpful to create opportunities in various business domains.     

Digital Twin-driven smart manufacturing: Connotation,reference model,applications and research issues

This paper reviews the recent development of Digital Twin technologies in manufacturing systems and processes, to analyze the connotation, application scenarios, and research issues of Digital Twin-driven smart manufacturing in the context of Industry 4.0. To understand Digital Twin and its future potential in manufacturing, we summarized the definition and state-of-the-art development outcomes of Digital Twin. Existing technologies for developing a Digital Twin for smart manufacturing are reviewed under a Digital Twin reference model to systematize the development methodology for Digital Twin. Representative applications are reviewed with a focus on the alignment with the proposed reference model. Outstanding research issues of developing Digital Twins for smart manufacturing are identified at the end of the paper.     

Data-driven cleaner production strategy for energy-intensive manufacturing industries: Case studies from Southern and Northern China

Cleaner production is an effective strategy for improving material utilization, reducing energy consumption, maximizing product output, and minimizing emissions during the entire manufacturing processes. An increasing number of enterprises promote the implementation of cleaner production. In the Industry 4.0 context, product-embedded information devices are widely used to capture product lifecycle data. Product lifecycle management provides an opportunity to achieve cleaner production strategy. This paper presents a data-driven cleaner production strategy by product lifecycle management for energy-intensive manufacturing industries. The data-driven strategy is proposed and explained by the lifecycle of cleaner production data. Implementation models are developed to illustrate the proposed data-driven cleaner production strategy. Furthermore, two case studies from Southern and Northern China are presented to demonstrate the strategy. Results show that the unit energy consumption and the energy cost of production in Company A are reduced by at least 3% after applying the proposed strategy. In addition, the “cradle-to-gate” lifecycle data analysis indicates that the costs of environmental pollution in Company B are diminished significantly. Finally, energy-intensive manufacturing companies in China are compared and evaluated, and the effectiveness of the proposed strategy is discussed.     

An overview of work analysis instruments for hybrid production workplaces

With increasing technological improvements, production processes are becoming more and more automated. Nevertheless, full automation is improbable in the medium term since human abilities cannot yet be completely replaced. Therefore, it is likely that so-called hybrid human–robot teams will assume the future production. This raises questions regarding the shaping of future production and the effects it will have on the employees, workstations, and the companies as a whole. The project “Work in the Industry of the Future” (ARIZ) addresses the entirely new cooperative relationship between man and technology in the Industry 4.0 and its impact on opportunities for the work force. To derive the requirements and effects of hybrid workplaces, an initial work analysis of existing workplaces with varying levels of technological enhancement (manual workplaces, workplaces with co-existing robots and fully automated workplaces) will be conducted. Multiple standardized work analysis instruments that vary in method, duration, level of analysis, and recorded characteristics already exist. This paper gives an overview of an assortment of these methods that can be used in production.