International Journal of Industrial Engineering and Engineering Management

A Postural Risk Assessment of Steamer Production Workers Using RULA and REBA

Vertic Eridani Budi Darmawan — 2024-06-30

The present study examined the work posture of the worker as a basis for correcting bad postures in the workplace.
Rapid Upper Limb Assessment (RULA) and Rapid Entire Body Assessment (REBA) methods are applied to evaluate
the postural risk assessment which is related to musculoskeletal disorders (MSDs). There are five workers at UD.
Sidoarjo National Ship is chosen to analyze the risk posture for this study. Based on observations and calculations at
UD. Sidorajo National Ship, it was found that workers were still using less than optimal methods or not supported by
ergonomic workstations. The study reveals that every worker in UD. Sidoarjo National Ship workstations have a risk
of getting MSDs. These indicated that the worker’s work posture was less ergonomic and required changes to lessen
the risk of MDSs.

Low Wear Rate Selection of Nylon 6-Boron Nitride (PA6/BN) Composite During Composite Development Using Grey Relational Analysis Through the Direct and Indirect Factors of Taguchi Method

Abdulganiyu Adegboyega Adekoya — 2024-06-30

Wear performance has been evaluated for mechanical equipment using normal load, sliding speed, and sliding distance, but aspect ratios have been traditionally ignored in the literature. Also, limited studies have analyzed wear performance with sparse information. In this study, a grey relational analysis (GRA) technique is proposed for the wear performance analysis of nylon 6/boron nitride composite using aspect ratios. A complete divergence is made from the literature where the aspect ratios of the particulate weight of the composite, normal load, sliding speed, and sliding distance are treated in direct and aspect ratios of 12 cases where the reciprocals of factors, their squares and cubes are considered. Results show that the proposed method of GRA is feasible and offers an adequate illustration of the indices of the parameters of the wear process as opposed to the present method of Taguchi that exists in the literature. A key result is from case 2, which shows that experimental trial 9 with the grey relational grade of 1.00 has the lowest wear rate. The corresponding values of the parameters are 0.05 of the 1/NL parameter, while the SD parameter is 500. This is interpreted as 0.05N-1 of the reciprocal of normal load and 500m for the sliding distance. The principal contribution of this research is the introduction of the grey relational analysis to reduce the wear rate of nylon 6-boron nitride composite. The proposed method is useful as a planning tool for the maintenance engineer to monitor the health of equipment in practice.

Energy-efficient No-idle Flowshop Scheduling Optimization Using African Vultures Algorithm

Yolanda Mega Risma — 2024-06-30

The issue of energy consumption is currently a major concern globally, especially in the industrial sector, where most of the energy demand comes from the manufacturing sector. To reduce energy consumption, one of the proposed strategies is to reduce the idle time between jobs on machines during the production process, known as No-Idle Permutation Flowshop Scheduling (NIPFSP). This research proposes the application of the African Vultures Optimization Algorithm (AVOA) as a solution to the energy consumption challenge in the case of production scheduling. The algorithm is examined in detail through a series of trials to obtain the most efficient work order in the production schedule, subject to careful setting of iteration and population parameters. The result of implementing the AVOA algorithm is then compared with the method used by the company in a scheduling case. The research findings show that AVOA significantly outperforms the method commonly used by the company, confirming its performance advantage in optimizing energy consumption in the context of production scheduling.

Techniques for Improving Genetic Algorithms in Solving Operating Room Scheduling Problems: An Integrative Review

Deny Ratna Yuniartha — 2024-06-30

Operating room scheduling is a complex process that involves various resources and takes the interests of many parties into consideration. The genetic algorithm is the frequently used metaheuristic algorithm to solve a large-size operating room scheduling problem. Many techniques have been developed to improve the genetic algorithms' performance in dealing with the operating room scheduling complexity. In this paper, we survey available literature to identify improvement techniques used at each stage of the genetic algorithm and capture the underlying problems. This review provides a mapping of improvement techniques in genetic algorithms correlating with the considered problems. The results can be employed by other researchers as a guide for future research in integrating a genetic algorithm or other population-based metaheuristic algorithm with a recent heuristic algorithm following the future directions of operating room scheduling research.

Optimizing the Parameters of Carbon Fiber Reinforced Plastic Composite Drilling Process Using Signal-to-noise Ratio-based Grey Wolf Optimization Algorithm

Emmanuel Oluwatobi Taiwo — 2024-06-30

This study aims to develop an optimization scheme that contributes to the production of carbon fiber-reinforced plastics using the grey wolf optimization approach. Different from other optimization schemes such as the Taguchi method, which takes some time to compute and use, this grey wolf optimization approach introduced a fast convergence scheme to reduce computation time thereby making its implementation in the factory very interesting. Data used for the analysis was obtained from a doctoral thesis via an experimental approach. Four responses were considered in this work, namely the torque, delamination at entry and exit, eccentricity and thrust force. A spreadsheet was used to implement the computational procedure of the grey wolf optimization algorithm. In using the wolves, at the initial level, the starting point was a zero where hunting had not begun and the prey had just entered the park, which is within the territory of the grey wolves. With this in mind, real life is mimicked and such data gathered would aid precise decision-making. The results revealed the feasibility of the approach and convergence was obtained at the tenth iteration with the best fitness value at 9020785071. It is expected that the findings from this work will be useful as a method for planning in production planning and policy development for the carbon fiber-reinforced plastic industry. This study is a noteworthy contribution to the production development of CFRPs where the grey wolf algorithm is used to analyze the problem. In addition, evidence of the responses determining the quality of drilled products is provided.