Ergonomics and simulation-based approach in improving facility layout

Journal of Industrial Engineering International https://doi.org/10.1007/s40092-018-0260-z (0123456789().,-volV)(0123456789(). ,- volV) ORIGINAL RESEARCH Ergonomics and simulation-based approach in improving facility layout Jocelyn D. Abad1 Received: 3 February 2017 / Accepted: 27 January 2018 Ó The Author(s) 2018. This article is an open access publication Abstract The use of the simulation-based technique in facility layout has been a choice in the industry due to its convenience and efficient generation of results. Nevertheless, the solutions generated are not capable of addressing delays due to worker’s health and safety which significantly impact overall operational efficiency. It is, therefore, critical to incorporate ergonomics in facility design. In this study, workstation analysis was incorporated into Promodel simulation to improve the facility layout of a garment manufacturing. To test the effectiveness of the method, existing and improved facility designs were measured using comprehensive risk level, efficiency, and productivity. Results indicated that the improved facility layout generated a decrease in comprehensive risk level and rapid upper limb assessment score; an increase of 78% in efficiency and 194% increase in productivity compared to existing design and thus proved that the approach is effective in attaining overall facility design improvement. Keywords Efficiency  Ergonomics  Facility design  Safety  Promodel Introduction Strong market competition sets pressure on companies to streamline their processes and achieve overall operational efficiency. Several techniques are found effective in improving operational efficiencies such as work measurement, ergonomics, and facility design. Kazerouni et al. (2015) concluded that facility design is a major factor in efficiency. Previous studies have developed several approaches to improve and resolve facility design problems. One approach is the heuristic method which includes tabu search (TS), genetic algorithms (GA), ant colony, simulated annealing (SA) and hybrid approaches. However, these approaches are time-consuming and focus on material handling cost and distance improvements and do not incorporate actual setting and dimension of machines and equipment (Sharma et al. 2013; Dwijayanti et al. 2010). Another approach is the use of simulation software such as Promodel, Arena, Quest, and IGrip, which are a & Jocelyn D. Abad 1 Department of Industrial Engineering, Technological Institute of the Philippines, Quezon City, Philippines more efficient and convenient method in evaluating facility layouts before implementation (Sharma et al. 2013). Nevertheless, both heuristic method and simulation are not capable of addressing inefficiencies due to worker’s health and safety. Therefore, it is critical not only to ensure the efficiency through facility design, but also to consider the health and safety of the employees (Kazerouni et al. 2015). Mustafa et al. (2009) discussed that the primary purpose of ergonomics is to ensure a good fit between the employees and their job to optimize worker’s comfort, safety and health, productivity and efficiency. Previous ergonomic studies have shown the relationship of workstation design in worker’s efficiency and safety. Shewchuk et al. (2017) provided a methodology in modeling and assessing the complex multi-worker physical processes which helped establish the ergonomic implications of the operations. Suhardi et al. (2016) improved the production process through ergonomic design. Other studies that applied ergonomics, workstation design and work system concepts include: the analysis on the effectiveness of the ergonomic prototype in reducing risks associated in a task (Fonseca et al. 2016); identification of work-related musculoskeletal disorders (WMSDs) using ergonomic 123 Journal of Industrial Engineering International assessment tools such as rapid upper limb assessment (RULA) and rapid entire body assessment (REBA) (Sahebagowda et al. 2016) and the methodological framework incorporating technological and environmental factors to improve productivity and ergonomics in an assembly system design (Battini and Faccio 2011). Table 1 summarizes the common techniques in improving facility layout, its purposes and, drawbacks. Although both the heuristic method and simulation approaches produce optimal or best layout, these were not capable of addressing the health and safety issues of the workers. Table 2 summarizes the previous developments in ergonomics and facility design. Several studies have focused on obtaining the optimal solution to solve facility layout problems, nevertheless have not considered the needs of workers. The goal of this study is to improve efficiency and productivity of the facility design and at the same time address inefficiencies caused by workers due to health and safety issues. Methodology Figure 1 illustrates the framework for improving facility layout through ergonomics and simulation-based approach. The methodology considers the variables related ergonomic risks, efficiency and productivity. To measure the productivity and efficiency, this study incorporated Promodel simulation software both for the existing and improved layouts. Rapid upper limb assessment (RULA) (McAtamney and Corlett 2004) was used to determine the ergonomic risks in each process as well as Fuzzy Risk Predictive Model (McCauley-Bell and Badiru 1996) in determining comprehensive risk levels in the workstations. Results and discussions Existing facility layout Process analysis revealed the delays in the operation specifically during the movement of the material. The cutter traveled around 28.39 m from sorting area to assembly area and vice versa. Moreover, from cutting operation, the worker traveled approximately 8.09 m going to sorting area. The existing layout did not show any concrete layout flow, which resulted in non-productive time due to the long distance traveled. Table 3 presents the simulation results of the existing facility layout. Using RULA, most of the workstations fell under Class IV (investigate and implement change) category. This indicated that the workstations were prone to ergonomic hazards and risks, which may affect worker’s performance and later on may result in musculoskeletal disorders (MSDs). McCauley-Bell and Badiru (1996) developed the fuzzy predictive model to quantitatively predict the risk level of work-related musculoskeletal disorders (WMSDs). Three risk factors were identified namely: task-related, personal and organizational risks and were evaluated for relative significance. Levels of existence for each risk factor are the following: high (1.00), medium (0.50), low (0.20) and nonexistence (0.00). The wn, xn and yn are relative weights for each factor and an, bn and cn are levels of existence for each factor. Relative weight for each risk factor is detailed in Table 4. Table 1 Comparison of conventional techniques in improving (...truncated)