In the context of Industry 5.0, socially sustainable manufacturing demands assembly systems that support diverse worker capabilities, including those of individuals with disabilities. This study investigates the impact of disability severity on system throughput and identifies which assembly configurations best promote inclusion while maintaining productivity. Using discrete event simulation, serial and parallel system flows were analysed under varying levels of product variability, buffer capacity, and worker impairment. Disability was modelled through two parameters: the increment of assembly time, representing the percentage increase in task duration for the disabled worker, and the percentage of station time executed by the disabled worker, capturing different levels of task involvement. Findings reveal that throughputs in serial systems decline sharply with higher disability severity, especially under conditions of high variability and limited buffering. In contrast, parallel flow systems exhibited greater resilience, sustaining higher performance despite severe impairments. Decision-tree analysis identified task time variability, the number of workstations, and extended task durations as critical factors in determining optimal system configurations. These effects were context-dependent and influenced by system layout. The results demonstrate that inclusive system design can be achieved without sacrificing efficiency, provided structural flexibility is embedded, especially via parallel processing strategies. This research underscores the importance of integrating flow strategy and task allocation approaches when including workers with diverse abilities, contributing to the broader vision of human-centred and inclusive manufacturing in Industry 5.0.

Human-robot interaction is becoming a prevalent design choice for workplaces. Robots can provide support in tasks and processes, while humans can provide flexibility in certain aspects. However, as seen in the literature reviews, the implementation of human-robot systems does not consider the effects on operators, which can increase mental demands and raise safety concerns. This work presents the results of an experimental study on human-robot collaboration, targeting the connection between cognitive load and quality of processes, products, and human work. The results show that the temporal demand of collaboration is one of the associated reasons behind cognitive load and stress. The authors use the demand-control model to understand the empirical results and provide design guidelines for engineers and practitioners to improve task and process design for collaborative robot systems. Future research directions are also provided.

Workers' risks to develop musculoskeletal disorders (MSD) are influenced by work-related and individual risk factors (RF). If workers have different levels of vulnerability (individual RF), managers face the decision whether to foster equality (an equal distribution of work-related RF levels) or equity (an equal distribution of net resulting MSD risk) when designing work plans. We use a mathematical model to assess the consequences of equality and equity policies for workers' MSD risks. We also aim at raising researchers' and practitioners' awareness for these kinds of questions. The model builds upon the assessment of workers' MSD risks using logistic regression. Applying the model to epidemiological data suggests that neither administrative risk control strategy provides a net benefit at the group level as risks can only be shifted between workers but not be reduced. These results suggest that real workforce level risk reductions may require engineering controls to reduce MSD risks.Practitioner summary: Existing epidemiological MSD risk evidence is used to analyse the impacts of policies of workload equality and injury risk equity. The policies have little impact on overall workforce MSD rates. This illustrates how administrative control policies may be ineffective at managing workforce injury risks. Engineering controls to reduce workload levels are recommended instead.

The evolution of Human-Robot Collaboration (HRC) has moved beyond simple task-sharing, progressing toward advanced systems that integrate cognitive and physical dimensions in a proactive approach. The prevailing research is increasingly emphasizing adaptive interaction, predictive intelligence, multimodal perception and mutual synchronization between humans and robots. In this study, a literature mapping review was conducted to capture the latest trends and practices in HRC design and control, also distinguishing human-centric from robot-centric approaches. The analysis identified five thematic clusters capturing the current trends, i.e.: (i) AI-driven cognitive augmentation; (ii) seamless safety; (iii) enhanced digital twins, augmented reality, and virtualization; (iv) multimodal perception and mutual awareness; and (v) robot humanization. A literature key gap emerged, i.e., the lack of a holistic, system-centric framework that comprehensively integrates both human and robotic perspectives, in system design and control principles as per the identified dimensions. To address the gap, the Human-Robot Embodiment paradigm is introduced and proposed as the evolution of proactive HRC, structured around three integrated dimensions: (a) Situational Awareness and Continual Learning, (b) Enactment and Entrainment and (c) Bidirectional Control. The paper concludes by outlining challenges, opportunities and future directions for implementing the unified HRE paradigm.

Human-centred design must be present during undergraduate engineering education to ensure graduates’ ability to meet ethical obligations safeguarding life, health, and public welfare. A pilot study of accredited Canadian engineering programs found Human Factors / Ergonomics (HFE)-content in only 14% of required courses. A complete survey of undergraduate engineering programs would likely find 20% incidence of HFE-content, however potential HFE keywords were discovered in 91%. This paper describes challenges to filtering courses with relevant HFE content while avoiding false positives. Published undergraduate course descriptions presented course content. Experts defined HFE relevant keywords, counted using MAXQDa software and in-house programs in Python and R, including their contexts without Artificial Intelligence. Manual review beyond automated keyboard counts, found certain keywords like “interface” to be problematic alone and others reliable (ergono*) but incomplete. This analysis reveals that potentially relevant keywords are insufficient indicators of HFE content. Limitations for other content evaluations are emphasized.

The integration of human factors and ergonomics (HF/E) into industrial and operational decision support modeling has grown rapidly over the past decade. In particular, physical aspects (e.g., physical workload, fatigue -recovery cycles) have been popular in developing human-centered solutions in operations management (OM). These solutions aim, first, to prevent both short- and long-term health issues among workers (e.g., work overload and occupational musculoskeletal disorders) and, second, to enhance the system performance of model-based solutions in real-world settings. However, adopting a human-centric perspective necessitates interdisciplinary knowledge. Specifically, each model or tool developed by ergonomists possesses unique characteristics (including the original experimental settings, the scope of collected data, and the intended application scenarios). They should thus be used with caution in managerial decision support models. To facilitate the knowledge transfer from HF/E to OM, this pilot study provides preliminary results of: (i) a scoping review of the integration of physical HF into decision support modeling in operations management; (ii) a critical evaluation of model assumptions and the interpretation of results from an HF/E perspective; and (iii) the development of a structural framework to suggest HF/E model choices. The current study presents preliminary results with an interdisciplinary perspective, which will be extended in future research. Copyright (c) 2025 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)

Professional engineers must ensure public welfare and environmental protection. Their undergraduate training, however, may not include the necessary Ergonomics and Human Factors (EHF) knowledge to succeed. This study describes the sufficiency of EHF presentation based on an international survey of professors with knowledge of EHF offerings in engineering undergraduate programs and the EHF presence based on relevant keywords in undergraduate university engineering course descriptions in Canada. Twenty-nine of the 37 survey respondents were affiliated with “systems” or “industrial” engineering programs and 36 believe EHF is at least “somewhat important” to engineering professionals. Perceived EHF presence by institution ranged widely from “insufficient” to “excellent” with the mid-point “good” appearing most frequently. A subset of 167 Canadian accredited undergraduate engineering programs showed wide variation of EHF keywords in course description with 144 (86

Work induced fatigue is associated with quality deficits, human-system errors, accidents, and injuries in the workplace, which in many industries may cause harm to employees and communities they serve. Managing physical fatigue requires tools that inform system design and management decisions. This research presents a method to quantify employee fatigue levels across multiple days. Physical workload time history from simulation provides inputs to empirically based endurance time and recovery models. Outputs include fatigue level indicators within and across multiple shifts. Three nursing example scenarios demonstrate the recovery needed over a two-week shift schedule in response to: (1) varying recovery efficiency between shifts; (2) nurse strength differences; and (3) shift scheduling changes. Scenarios showed the impact of fatigue accumulation and time spent needing recovery or time fully recovered due to competing interests outside of work, individual differences, as well as organisational influences on work scheduling. While further research is needed, the proposed method can provide work system designers and managers with critical information about employee fatigue consequences for operational and design decisions in work systems. This information is crucial for the design of safe, effective, and sustainable high-quality performance in Industry 5.0 systems.

The aim of this paper is to enhance readers' understanding of research design strategies, past and present, for studying nursing workloads. Future research directions are also discussed. Nursing workloads are associated with nurse burnout and turnover. During our current global nursing shortage, researchers must identify ways to mitigate nurses' heavy workloads. Relevant, prior nursing workload research is presented with brief descriptions of designs, methods and findings. To illustrate the current complexity of nurses' work environments and the myriad factors that influence nurses' workloads, this paper features the ongoing nursing workload research of two Canadian research teams with different methodological approaches. These two teams are employing current research innovations, such as human factors multi-systems frameworks, design thinking, simulation modeling and integrated knowledge translation. With respect to future research implications, the teams are melding methods and tools to promote a more sophisticated way of understanding the complex linkages between patient needs, systems design and the management of nurses' workloads.

This study uses Digital Human Modelling (DHM) and Discrete Event Simulation (DES) to examine how caring for COVID-19-positive (C+) patients affects nurses' workload and care-quality. DHM inputs include: nurse anthropometrics, task postures, and hand forces. DES inputs include: unit-layout, patient care data, COVID-19 status & impact on tasks, and task execution-logic. The study shows that reducing nurses' biomechanical workload increases mental workload and decreases direct patient care, potentially leading to stress, burnout, and errors. Compared to pre-pandemic conditions, when nurses were assigned five C+ patients, cumulative bilateral shoulder moments and lumbar load decreased by 38%, 36%, and 46%, respectively. However, this was accompanied by increases in mental workload (242%), task waiting-time (70%), and missed-care (353%). These effects were driven by the large increase in required infection control routines. Combining DHM and DES can help evaluate workplace/task designs and provide valuable insights for healthcare system design-policy setting and operational management decision-making.

One of the United Nations' Sustainable Development Goals is focused on decent work and growth which aims to reduce and, finally, remove all barriers for people with a form of diversity like disability. In such a context, manufacturing and production systems should be adapted by adopting specific equipment to help workers with disability while executing jobs according to the type of disability they report. Jobs must be properly planned since disabled workers have physical or cognitive disabilities and specific rights to work. Further, aiming to guarantee a real inclusion of workers with disability production systems should be designed to include these workers in the same working environment as workers without disability. This paper focuses on assembly systems, and it aims to investigate how different designs could impact both the productivity and inclusion of disabled workers. Then, due to the higher variety of products belonging to the same family mixed model assembly systems are considered. For each assembly system design, the daily productivity is calculated by using a simulation approach Finally, according to the obtained results we provide some considerations about the convenience of adopting parallel flows to guarantee higher inclusion without affecting too much the productivity of the assembly system. Copyright (C) 2024 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)

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Interaction between humans and robots in the workplace garners interest in recent years due to the introduction of Industry 4.0 and Industry 5.0 frameworks. A scoping review was performed aimed at investigating the effect of robot design features on their human counterparts. In the analysis of the 32 identified articles, the robot design features used in the literature are shown along with the effects on the operators. Results showcased the many to many relationships between robot design features and effects on operators. Robot appearance, for example, and capabilities play a role in the operators’ perception and expectations of their capabilities based on the task and subsequently perceived reliability and safety. Communication capabilities between operators and robots is an integral part for teamwork and performance as it can affect work processes. The paucity of papers empirically addressing human robot interaction as a system is consistent with results from previous literature, indicating the need for more research. The results of this investigation can prove useful in the form of advice to designers and practitioners, such as the operator’s involvement in implementation, knowledge on robots’ capabilities and training. Research gaps identified are discussed, as well as future research directions.

Background Worldwide, the worker population age is growing at an increasing rate. Consequently, government institutions and companies are being tasked to find new ways to address age-related workforce management challenges and opportunities. The development of age-friendly working environments to enhance ageing workforce inclusion and diversity has become a current management and national policy imperative. Since an ageing workforce population is a spreading worldwide trend, an identification and analysis of worker age related best practices across different countries would help the development of novel palliative paradigms and initiatives. Methods This study proposes a new systematic research-based roadmap that aims to support executives and administrators in implementing an age-inclusive workforce management program. The roadmap integrates and builds on published literature, best practices, and international policies and initiatives that were identified, collected, and analysed by the authors. The roadmap provides a critical comparison of age-inclusive management practices and policies at three different levels of intervention: international, country, and company. Data collection and analysis was conducted simultaneously across eight countries: Canada, France, Germany, Italy, Japan, New Zealand, Slovenia, and the USA. Results and conclusions The findings of this research guide the development of a framework and roadmap to help manage the challenges and opportunities of an ageing workforce in moving towards a more sustainable, inclusive, and resilient labour force.

Human robot collaboration is becoming the norm in the workplace, due to the benefits robots can bring to efficiency and production. However, this creates highly complex and dynamic workplaces that human operators need to adapt to. Industry 5.0 promotes the use of robotics and smart technologies in a more human-centric way. However, research on how operators are affected by those changes is needed to better understand how to move towards human-centricity. As such, an experimental study was designed and performed on human robot collaborative assembly. The main aim was to investigate the correlation between cognitive load and quality due to collaboration. Here, the preliminary results of the experimental study are presented in order to remark relevant states influencing work allocation. The results showcased the need for better training and more knowledge for the operators, as well as involving operators in process and workplace design. This study helps contribute knowledge on robot implementation and process design for human robot collaboration for both researchers and operations management, as it showcases the need to involve operators in those steps due to the feedback they can provide due to their experience.

This study proposes a generic approach for creating human factors-based assessment tools to enhance operational system quality by reducing errors. The approach was driven by experiences and lessons learned in creating the warehouse error prevention (WEP) tool and other system engineering tools. The generic approach consists of 1) identifying tool objectives, 2) identifying system failure modes, 3) specifying design-related quality risk factors for each failure mode, 4) designing the tool, 5) conducting user evaluations, and 6) validating the tool. The WEP tool exemplifies this approach and identifies human factors related to design flaws associated with quality risk factors in warehouse operations. The WEP tool can be used at the initial stage of design or later for process improvement and training. While this process can be adapted for various contexts, further study is necessary to support the teams in creating tools to identify design-related human factors contributing to quality issues.

The objective of this work is to develop better understandings of the current trends in corporate strategy and production system design and the consequences these trends can have for the musculoskeletal health of production system operators.

This research examines the status of human factors and ergonomics (HF/E) metrics in the case context of product realisation in an electronics manufacturing company. Interactions with 100+ stakeholders over a five year period were thematically analysed for metrics-related views and content. A disconnect between engineering metrics and HF/E metrics was evident. Engineers and HF/E specialists expressed different understandings of the gap between the disciplines and how to generate HF/E metrics that would fit the organisation. Other emerging themes provided insight for metrics development including improving indicator relatability, considerations for communication of information, and barriers to implementation of metrics. The results led to seven recommendations to help guide practitioners in developing and refining HF/E metrics as part of an organisation's metrics system. This macroergonomic case study provides key points for consideration when developing HF/E focussed metrics to support organisations being more proactive with HF/E in work system design. Practitioner summary: Metrics' presence, stakeholder views on metrics, and metrics-related content in a case organisation were thematically analysed with a macroergonomics focus. Human factors and ergonomics metrics (HF/E) were disconnected from engineering metrics thus limiting the design team's ability to handle human factors in design. Factors influencing HF/E metrics creation and integration were identified, resulting in seven recommendations for developing HF/E metrics.