Scheduling Customized Orders by Considering the Ergonomic Constraints: A Case Study at YEMTAR Company

Abstract

It is important for companies to meet customer demands by due date and reduce the labor cost on the finalized product. For this purpose, order scheduling is required for different purposes such as minimizing makespan, maximizing resource utilization, etc. Dynamic production environment causes stochastic operation times at companies which work based on project type labor-intensive production. Stochastic operation times make order scheduling harder. There are many reasons that causes operation times being stochastic such as technical specifications of the orders, skills of the operators, bottlenecks in the job-shop, and etc. However, one of the most important but less discussed constraints that affect the probability distribution of the operation times is the ergonomic constraint. Ergonomic constraints, such as musculoskeletal discomfort, fatigue and limitations determined by the laws make it even more difficult to predict the total makespan of waiting orders. In this study, an order scheduling algorithm that considers the dynamical production environment and the ergonomic limitations is proposed for nearly optimizing average makespan for several waiting orders in the grinding and painting workstation of YEMTAR Company. The proposed algorithm adopts the technical order specifications and ergonomic constraints together, computes the stochastic operation times by using simulation, and schedule orders by using genetic algorithm. The objective is to determine the entry sequence of the waiting orders to the workshop for minimizing their average makespan which directly influences the resource utilization, efficiency, and labor costs.

Optimization of welding job-shop scheduling problem under variable workstation constraint: an industrial application with Arena simulation based genetic algorithm

“…Arena is run to measure processing times of the orders and also to calculate the makespan of operations depend on GA-generated order sequences. Please refer to [28], [29] for a detailed discussion on GA and also refer to [7], [13] for a detailed discussion on simulation based GA. JSSP is well-known as NP hard problem.…”

“…In order to integrate directly with other systems such as Microsoft Office, Arena uses 'Visual Basic for Applications' (VBA) editor. Arena 14 is used as the simulation software in this paper for the simulation [7], [13], [33].…”

“…For the crossover strategy; two point crossover is used [7]. The pseudocode for this GA aided simulation method is given in Figure 2 [7], [13]. A sample result of this code is given in Figure 3.…”

“…They considered energy consumption, low carbon emissions, and makespan as the performance criteria. Karaoglan et al [13] studied on JSSP by considering the ergonomic constraints. They used combined GA and Arena simulation to minimize the makespan.…”