Högskolan i Skövde

In industry, simulation software is used to simulate production, making it possible to predict events in production, calculate times and plan production, even in the early phases of the production development process. Software known as digital human modelling (DHM) tools can also be used to simulate humans working in production. When simulating digital human models, ergonomics evaluations can be carried out to assess whether workstation designs offer appropriate ergonomic conditions for the workers. However, simulations performed to predict and plan production are usually done separately from the human simulations performed to evaluate ergonomics. This can lead to suboptimal solutions in which a factory is optimized to improve either productivity or ergonomics. This thesis outlines the hypothesis that more optimal solutions for workstation design, layout and line balancing can be obtained in simulations by optimizing productivity and ergonomic factors simultaneously instead of considering them separately. Hence, the aim is to carry out research on the development of a simulation-based multi-objective optimization method for productivity and ergonomic factors and to realize the method as a software tool in order to test and communicate it. From an application and societal-impact perspective, the overall objective is to offer a new approach for designing production systems that focuses on both over-all system performance and the well-being of workers, reduces the effort of engineers and helps industry create more productive and sustainable workspaces.

OCCUPATIONAL APPLICATIONS

Worker well-being and overall system performance are important elements in the design of production lines. However, studies of industry practice show that current design tools are unable to consider concurrently both productivity aspects (e.g., line balancing and cycle time) and worker well-being related aspects (e.g., the risk of musculoskeletal disorders). Current practice also fails to account for anthropometric diversity in the workforce and does not use the potential of multi-objective simulation-based optimization techniques. Accordingly, a framework consisting of a workflow and a digital tool was designed to assist in the proactive design of workstations to accommodate worker well-being and productivity. This framework uses state-of-the-art optimization techniques to make it easier and quicker for designers to find successful workplace design solutions. A case study to demonstrate the framework is provided

TECHNICAL ABSTRACT

Rationale: Simulation technologies are used widely in industry as they enable efficient creation, testing, and optimization of the design of products and production systems in virtual worlds. Simulations of productivity and ergonomics help companies to find optimized solutions that maintain profitability, output, quality, and worker well-being. However, these two types of simulations are typically carried out using separate tools, by persons with different roles, with different objectives. Silo effects can result, leading to slow development processes and suboptimal solutions.

Purpose: This research is related to the realization of a framework that enables the concurrent optimization of worker well-being and productivity. The framework demonstrates how digital human modeling can contribute to Ergonomics 4.0 and support a human factors centered approach in Industry 4.0. The framework also facilitates consideration of anthropometric diversity in the user group.

Methods: Design and creation methodology was used to create a framework that was applied to a case study, formulated together with industry partners, to demonstrate the functionality of the noted framework.

Results: The framework workflow has three parts: (1) Problem definition and creation of the optimization model; (2) Optimization process; and (3) Presentation and selection of results. The case study shows how the framework was used to find a workstation design optimized for both productivity and worker well-being for a diverse group of workers.

Conclusions: The framework presented allows for multi-objective optimizations of both worker well-being and productivity and was successfully applied in a welding gun use case.

Simulation software is used in the production development process to simulate production and predict behaviors, calculate times, and plan production in advance. Digital human modeling (DHM) software is used to simulate humans working in production and assess whether workstation designs offer appropriate ergonomic conditions for the workers. However, these human simulations are usually carried out by human factors engineers or ergonomists, whereas the production simulations are carried out by production engineers. Lack of integration of these two simulations can lead to suboptimal solutions when the factory is not optimized to improve both productivity and ergonomics. To tackle this problem, a platform has been developed that connects production flow simulation software data and DHM software data and integrates them in a generic software for data treatment and visualization. Production flow simulation software data and DHM software data are organized in a hierarchical structure that allows synchronization between the production data and the ergonomic data on the target simulation software. The platform is generic and can be connected to any production flow simulation software and any DHM software by creating specific links for each software. The platform requires only the models of the production line, workstations, and tasks in order to perform the simulations in the target simulation software and collect the simulation results to present the results to the user of the platform. 

Simulation technologies are widely used in industry as they enable efficient creation, testing, and optimization of the design of products and production systems in virtual worlds, rather than creating,testing, and optimizing prototypes in the physical world. In an industrial production context, simulation of productivity and ergonomics helps companies to find and realize optimized solutions that uphold profitability, output, quality, and worker well-being in their production facilities. However, these two types of simulations are typically carried out using separate software, used by different users, with different objectives. This easily causes silo effects, leading to slow development processes and sub-optimal solutions. This paper reports on research related to the realization of an optimization framework that enables the concurrent optimization of aspects relating to both ergonomics and productivity. The framework is meant to facilitate the inclusion of Ergonomics 4.0 in the Industry 4.0 revolution.

Simulations of future production systems enable engineers to find effective and efficient design solutions with fewer physical prototypes and fewer reconstructions. This can save development time and money and be more sustainable. Better design solutions can be found by linking simulations to multiobjective optimization methods to optimize multiple design objectives. When production systems involve manual work, humans and human activity should be included in the simulation. This can be done using digital human modeling (DHM) software which simulates humans and human activities and can be used to evaluate ergonomic conditions. This paper addresses challenges related to including existing ergonomics evaluation methods in the optimization framework. This challenge arises because ergonomics evaluation methods are typically developed to enable people to investigate ergonomic conditions by observing real work situations. The methods are rarely developed to be used by computer algorithms to draw conclusions about ergonomic conditions. This paper investigates how to adapt ergonomics evaluation methods to implement the results as objectives in the optimization framework. This paper presents a use case of optimizing a workstation using two different approaches: 1) an observational ergonomics evaluation method, and 2) a direct measurement method. Both approaches optimized two objectives: the average ergonomics results, and the 90th percentile ergonomics results.

Work-related musculoskeletal disorders (WMSDs) are often associated with high costs for manufacturing companies and society, as well as negative effects on sustainable working life of workers. To both ensure workers’ well-being and reduce the costs of WMSDs, it is important to consider worker well-being in the design and operations of production processes. To facilitate the simulation of humans in production and improve worker well-being, there are numerous digital human modelling (DHM) tools available on the market. Besides simulation of humans in production, there are numerous production simulation software to simulate production flows of factories, robots and workstations that offer the possibility of improving the productivity of the stations, optimizing the layout and the configuration of the production lines. Despite of the capabilities of DHM and production flow simulation software, there is a lack of tools that can handle an overall optimization perspective, where it is possible to concurrently treat aspects related to both worker well-being and productivity within one tool. This study presents a prescribed tool that enables concurrent multi-objective optimization of worker well-being and productivity in DHM tools by analyzing the impact of different design alternatives. The tool was assessed in a workstation layout optimization use case. In the use case, risk scores of an ergonomics evaluation method was used as a measure of well-being, and total walking distance and workstation area were used as measures of productivity. The results show that the optimized solutions improve both total walking distance, workstation area and ergonomic risk scores compared to the initial solution. This study suggests that the concurrent multi-objective optimization of worker well-being and productivity could generate more optimal solutions for industry and increase the likelihood for a sustainable working life of workers. Therefore, further studies in this field are claimed to be beneficial to industry, society and workers.

Usually, optimizing productivity and optimizing worker well-being are separate tasks performed by engineers with different roles and goals using different tools. This results in a silo effect which can lead to a slow development process and suboptimal solutions, with one of the objectives, either productivity or worker well-being, being given precedence. Moreover, studies often focus on finding the best solutions for a particular use case, and once solutions have been identified and one has been implemented, the engineers move on to analyzing the next use case. However, the knowledge obtained from previous use cases could be used to find rules of thumb for similar use cases without needing to perform new optimizations. In this study, we employed the use of data mining methods to obtain knowledge from a real-world optimization dataset of multi-objective optimizations of worker well-being and productivity with the aim to identify actionable insights for the current and future optimization cases. Using different analysis and data mining methods on the database revealed rules, as well as the relative importance of the design variables of a workstation. The generated rules have been used to identify measures to improve the welding gun workstation design.

There is a constant strive in industry to be competitive on the market, to manufacture with quality and productivity. At the same time, it is important to offer workers a sustainable work life. Research has shown a clear relationship between poor ergonomics and productivity losses and quality deficiencies, e.g. due to assembly errors, which also causes large costs for companies. In spite of the abovementioned relationship, productivity, ergonomics and quality are commonly treated separately in factory, line and workstation planning. To improve the factory, line and workstation planning, make it more efficient, ergonomic and to improve quality this paper proposes a concept that enables line balancing that considers two parameters in parallel, assembly time and ergonomic load as well as add possibility for mathematical optimization. The concept has been developed in a participative and iterative process. Two software tools and a simulation platform, the digital human modelling tool IPS IMMA, the balancing tool AVIX and the optimization platform EPP, have been used to demonstrate the concept. An integrated solution is formed. The integrated demonstration tool shows promising results. The demonstrator provides the possibility to manually optimize ergonomics and time in parallel, a relatively unique functionality.