A framework to design a human-centred adaptive manufacturing system for aging workers

The so-called smart manufacturing systems (SMS) combine smart manufacturing technologies, cyber-physical infrastructures, and data control to realize predictive and adaptive behaviours. In this context, industrial research focused mainly on improving the manufacturing system performance, almost neglecting human factors (HF) and their relation to the production systems. However, in order to create an effective smart factory context, human performance should be included to drive smart system adaptation in efficient and effective way, also by exploiting the linkages between tangible and intangible entities offered by Industry 4.0. Furthermore, modern companies are facing another interesting trend: aging workers. The age of workers is generally growing up and, consequently, the percentage of working 45–64 years old population with different needs, capabilities, and reactions, is increasing. This research focuses on the design of human-centred adaptive manufacturing systems (AMS) for the modern companies, where aging workers are more and more common. In particular, it defines a methodology to design AMS able to adapt to the aging workers’ needs considering their reduced workability, due to both physical and cognitive functional decrease, with the final aim to improve the human-machine interaction and the workers’ wellbeing. The paper finally presents an industrial case study focusing on the woodworking sector, where an existing machine has been re-designed to define a new human-centred AMS. The new machine has been engineered and prototyped by adopting cyber-physical systems (CPS) and pervasive technologies to smartly adapt the machine behaviour to the working conditions and the specific workers’ skills, tasks, and cognitive-physical abilities, with the final aim to support aging workers. The achieved benefits were expressed in terms of system usability, focusing on human-interaction quality.     

Situation awareness,human error,and organizational learning in sociotechnical systems

In many organizations, the performance of individuals and teams is negatively affected by human error. Studies have shown that these errors can be reduced or even prevented by learning from them and by developing an understanding of error causation and its consequences. The ability to detect, understand, and anticipate errors refers to situation awareness (SA). Although SA is not limited to human error and it is more closely linked with decision making, it is a prerequisite for error reduction in complex sociotechnical work settings. The main objectives of this study were threefold: First, a model that can explain the interrelations between human error, SA, and organizational learning in sociotechnical systems was developed. Secondly, functional and dysfunctional factors that affect human error, SA, and organizational learning were identified. Thirdly, a research methodology was selected and adapted to empirically test the model in a real‐world sociotechnical task environment. To do so, an SA performance test and a human error questionnaire were used to examine SA and respective learning modes of 108 assembly‐line workers in the manufacturing industry. The final test results supported the central assumptions of the applied model. The article concludes by discussing applications in the field of sociotechnical systems analysis, team training, human performance programs, and high‐reliability organizations.     

Enhancing industrial performance: experiences of integrating the human factor

Abstract

Enhancing Industrial Performance refers to the case book that focuses on the effective implementation of sociotechnical innovation, describing real experiences with the management of the human-computer interface. It argues for an ergonomic approach to systems design and evaluation; human factors audits in systems prototyping; user participation in the design process; human-centred organizational design; and matching human resources with technological investment. In the paper, four case studies out of 15 are briefly described. It is stressed that the human-oriented design approach should be integrated in a company-wide manufacturing excellence programme. Finally, industry as well as universities need case studies.     

Humans: the missing link in manufacturing simulation?

Computer based discrete event simulation (DES) is one of the most commonly used aids for the design of automotive manufacturing systems. However, DES tools represent machines in extensive detail, while only representing workers as simple resources. This presents a problem when modelling systems with a highly manual work content, such as an assembly line. This paper describes research at Cranfield University, in collaboration with the Ford Motor Company, founded on the assumption that human variation is the cause of a large percentage of the disparity between simulation predictions and real world performance. The research aims to improve the accuracy and reliability of simulation prediction by including models of human factors.     

基于几何可靠性机器模型的装配系统实时性能分析

装配系统是生产系统的基本结构之一, 广泛应用于汽车、电器、电子产品等实际生产环境中.与传统的串行生产线取得的研究成果相比, 装配系统的研究, 特别是对系统暂态过程的实时性能分析的研究仍然未得到深入探讨.本文针对具有三台几何可靠性机器模型和有限缓冲区容量框架下的装配系统, 首先建立了用于此类系统暂态性能分析的数学模型, 通过马尔科夫方法导出了系统性能分析的解析公式.然后, 提出了一种基于分解的性能评估算法来近似系统的实时性能.具体来说, 本文推导出了用于计算具有三台几何可靠性机器模型的装配系统的实时生产率、消耗率、在制品数量, 以及完成一个生产批次所需时间的解析表达式.最后, 通过数值实验对所提出算法的准确性进行验证.     

Mapping workers’ performance to analyse workers heterogeneity under different workflow policies

Manual work in assembly lines allows one to benefit from human reasoning capabilities and to assure the flexibility to adapt to fluctuations in production volume, products mix and reduced product lifecycles. With the objective of quantifying and systematizing the knowledge about the heterogeneity of workers’ performance, data was collected in an industrial setting. The results demonstrate a significant variation in workers’ performance in terms of speed and variability of the task completion time. A mapping approach is proposed aiming to quantify the workers’ performance and visualize performance patterns. Since the human performance is influenced by the setting where the workers perform their job, two real assembly line pacing mechanisms were set and studied: pacing derived from the manual assembly system rhythm and pacing imposed by a fixed time constraint. The type of pacing clearly influences workers’ performance (i.e., speed and variability) and revealed a significant influence in the assembly line output. In particular, imposing a fixed and equal time constraint for every worker reduces the heterogeneity of workers’ performance and improves the assembly line output.     

Parallel Manufacturing for Industrial Metaverses: A New Paradigm in Smart Manufacturing

To tackle the complexity of human and social factors in manufacturing systems, parallel manufacturing for industrial metaverses is proposed as a new paradigm in smart manufacturing for effective and efficient operations of those systems, where Cyber-Physical-Social Systems (CPSSs) and the Internet of Minds (IoM) are regarded as its infrastructures and the "Artificial systems", "Computational experiments" and "Parallel execution" (ACP) method is its methodological foundation for parallel evolution, closed-loop feedback, and collaborative optimization. In parallel manufacturing, social demands are analyzed and extracted from social intelligence for product R & D and production planning, and digital workers and robotic workers perform the majority of the physical and mental work instead of human workers, contributing to the realization of low-cost, high-efficiency and zero-inventory manufacturing. A variety of advanced technologies such as Knowledge Automation (KA), blockchain, crowdsourcing and Decentralized Autonomous Organizations (DAOs) provide powerful support for the construction of parallel manufacturing, which holds the promise of breaking the constraints of resource and capacity, and the limitations of time and space. Finally, the effectiveness of parallel manufacturing is verified by taking the workflow of customized shoes as a case, especially the unmanned production line named FlexVega.      

Analysis of a linear walking worker line using a combination of computer simulation and mathematical modeling approaches

It has become increasingly important in the last few years to develop rapid, dynamic, responsive and reconfigurable manufacturing processes and systems. This is because manufacturing enterprises are now being forced to develop and constantly improve their production systems so that they can quickly and economically react to unpredictable conditions such as varying production volumes and product variants with small lot size, high quality and low costs. One effective method to achieve this is to create a more flexible, highly skilled and agile workforce capable to perform multiple or all the required tasks in a production area where the system can be reconfigured easily as needed to accommodate changes of production requirement on a daily or weekly basis.This paper presents a study of a so-called linear walking worker assembly line based on a combination of computer simulation and mathematical analysis. The linear walking worker assembly line is a flexible assembly system where each worker travels down the line carrying out each assembly task at each station; and each worker accomplishes the assembly of a unit from start to finish. This design attempts to combine the flexibility of the U-shaped moving worker assembly cell with the efficiency of the conventional fixed worker assembly line. The paper aims to evaluate one critical factor of in-progress waiting time that affects the overall system performance providing a dynamic simulation outlook as well as an insight into the mechanism of such a flexible and reconfigurable manufacturing system.     

Human motion prediction for human-robot collaboration

In human-robot collaborative manufacturing, industrial robots would work alongside human workers who jointly perform the assigned tasks seamlessly. A human-robot collaborative manufacturing system is more customised and flexible than conventional manufacturing systems. In the area of assembly, a practical human-robot collaborative assembly system should be able to predict a human worker’s intention and assist human during assembly operations. In response to the requirement, this research proposes a new human-robot collaborative system design. The primary focus of the paper is to model product assembly tasks as a sequence of human motions. Existing human motion recognition techniques are applied to recognise the human motions. Hidden Markov model is used in the motion sequence to generate a motion transition probability matrix. Based on the result, human motion prediction becomes possible. The predicted human motions are evaluated and applied in task-level human-robot collaborative assembly.     

A performance comparison between Kanban and CONWIP controlled assembly systems

There exists controversy on the superiority of logistics control systems. Kanban and CONWIP systems are focused on and analyzed in this paper. CONWIP is a well-known production control system, and some papers have shown it has better performance than the Kanban system. Our research shows that the Kanban is more flexible for the assembly system under concern with respect to a given objective than the CONWIP. In some cases, if the number of kanbans at each manufacturing/assembling station is optimally set, Kanban system outperforms CONWIP with a lower average WIP and the same level of throughput. That is, the distribution of kanbans can be an important design parameter of the system. We also propose two different policies to release cards in a CONWIP controlled assembly system, followed by their comparison results.     

Toward a new generic behavior model for human centered system simulation

The simulation of Human Centered Systems (HCS) has attracted increasingly attention in recent research. These systems involve individuals playing key roles, such as workers in manufacturing systems, soldiers in military operations, and investors in stock markets. The complexity simulating such systems is due to the need for modeling individual and group behavior and the integration of psychological and socio-technical aspects that can affect individual and HCS global performance. Although several models have been proposed to simulate such systems, most of them suffer from limitations pertaining to the integration of some factors, an inadequacy that will be discussed and elaborated on in this paper. The current study presents a new model for HCS simulation based on recent social and psychological theories. A model implementation example involving the simulation of a manufacturing system, considered as a HCS, is presented.     

Designing for operations: Towards a sociotechnical systems and cognitive engineering approach to concurrent engineering

In the practice of concurrent engineering, the factors that are considered early in the product design process include manufacturability, assembly, and cost. A set of issues that are not typically considered revolve around the operational requirements for human workers in the manufacturing system. What tasks will human workers accomplish? How will these tasks be organized and coordinated? What information and resources need to be shared? Will the workers have a coherent set of job responsibilities? How should the manufacturing environment be designed to support effective work practices? How can a manufacturing process be designed that also informs organizational structure and takes into account the quality of working life?

The field of sociotechnical systems theory (STS) focuses on exactly these kinds of issues. Rather than subscribing to the usual view of technological determinism — that a complex human-machine system is designed solely with respect to optimization of technical criteria — the goal of STS is to jointly optimize both human and technological considerations in system design and operation. The spirit of STS has much in common with recent work in cognitive systems engineering that advocates the design of joint cognitive systems in which machines serve as flexible, context-sensitive resources for human problem solving. Furthermore, a focus on design teams necessitates the study of the relationship between group work and technology as studied in the field of computer-supported cooperative work (CSCW). This paper briefly reviews current research in sociotechnical systems theory, computer-supported cooperative work, and cognitive systems engineering and proposes a framework for integrating operational concerns into the concurrent engineering process. Relevance to industry

To be competitive, organizations need to effectively manage human and technological resources. A key issue is the nature of the information and technological infrastructure that both enables and supports ‘best practice’ across the enterprise. This paper describes such an approach in the context of the ‘operational enterprise’ and provides both a philosophical stance as well as specific examples of software support.     

Intelligent planning of Grafcet charts

Manufacturing systems are entering a new age in which the demands of a market in continuous change impose their conditions on production processes. In this new generation, both the response capability to these demands and a reliable production process are aspects that are receiving most attention and study. One of the stages that can most affect these terms of reliability and time response is the development of the control program which drives the operation of the manufacturing system, although this subject has received little attention in the literature. This work provides a new effort in this direction and presents MACHINE, an artificial intelligence planner able to automatically obtain Grafcet charts for manufacturing systems.     

Reconfiguration of assembly systems: From conveyor assembly line to serus

Confronted with the dynamic and complex market environments, the traditional conveyor assembly line can no longer meet customers’ demands effectively. The way of reconfiguring conveyor assembly line to a more flexible manufacturing system has been attracting considerable attention both in the academics and production practices. Seru system, also called assembly cell system, is regarded as one of the most successful innovations of manufacturing system in reconfiguring conveyor assembly line. Such a manufacturing system merges considerable flexibility of job shops and high efficiency of conveyor assembly lines to some extent. In this paper, we investigate the problem of how to reconfigure conveyor assembly line to serus. A comprehensive mathematical model incorporating two issues of how many serus should be established and how many workers should be assigned to each seru is developed. Then the model is investigated by an industrial case and compared to Kaku's model with respect to the selected plan. The computation results validate that the proposed model is more suitable to analyze the reconfiguration problems from conveyor assembly line to serus.     

Modeling and solving assembly line design problems by considering human factors with a real‐life application

Ergonomics has been playing an important role in assembly system design (ASD) that contains not only the main assembly line balancing problem but also the subassembly line balancing and assembly layout problem. The ergonomics in ASD has an impact both on productivity and on workers’ health, especially when frequent changes in the product mix occur. In this study, we propose a systematic approach in order to handle ASD, which consists of three subproblems, while considering ergonomic risk factors. The first two subproblems are solved simultaneously using the proposed rule‐based constructive search algorithm, where ergonomic risks are evaluated by OCRA method. Later, layout problem is solved under transportation constraints using local search methods with various neighborhood structures. To provide the applicability and evaluate the performance of the proposed systematic approach, a real‐life case study in a harness manufacturing company is solved and prototype productions are performed.     

Integrating workers’ differences into workforce planning

In today’s competitive market, manufacturers need to work hard towards improving their production system performance in order to satisfy customer demands. In such a situation, most companies develop production systems that can help in quality improvement, cost reduction and throughput time reduction. In this research, we consider a workforce planning (WP) model including some human aspects such as skills, training, and workers’ personalities and motivation. A multi-objective non-linear programming model is developed in order to minimize the hiring, firing, training and overtime costs and minimize the number of fired most productive workers. The purpose is to determine the number of workers for each worker type, the number of workers trained, and the number of overtime hours. Moreover, a decision support system (DSS) based on the proposed model is introduced using the Excel-LINGO software interfacing feature. The results indicate that the proposed model can provide a promising workforce planning approach to easily apply it in practice.     

Manufacturing assembly serial and cells layouts impact on rest breaks and workers’ health

Rest breaks are necessary for workers to avoid and/or recover from overall fatigue and to preserve their health. The type of assembly layout, either in lines or in cells, is a determining factor for organizing work at manufacturing companies, and it could also influence workers' work break and microbreak times. This study aimed at evaluating rest breaks in serial and cell assembly layout configurations as well as the layout's influence on workers' health. One hundred and twenty workers from a large automobile industry, divided into two groups (series and cells), were measured for their cycle-times and break times through biomechanical exposure analysis and questionnaires to evaluate the behaviors, physical, cognitive, and mental health. The Kolmogorov-Smirnov test was used to verify the distribution of the data with a significance level of p < 0.05. The cell assembly-line layouts had the greatest cycle-time and break time, and the workers had a higher level of physical activity (p < 0.05). The serial assembly-line layouts did not generate major occupational risk, need for rest, reduced capacity for work, or higher levels of stress for the workers. The production layouts differed in relation to the cycle-times for just-in-time manufacturing, but there was no difference in relation to the production demands and to the workers' health.Relevance to industryWhen taken at appropriate times, rest breaks in the workplace can improve workers’ overall health and productive performance, which reduces healthcare costs and improves industrial productivity.