An evaluation model for task complexity in production lines

Song Thanh Quynh Le and Huynh Van Nam

International Journal of Productivity and Performance Management, 2022, vol. 72, issue 10, 3162-3183

Abstract: Purpose - Task complexity is one of the significant factors that influences and is used for forecasting employee performance and determining labor cost. However, the complexity level of tasks is unstructured, dynamic and complicated to perform. This paper develops a new method for evaluating the complexity level of tasks in the production process to support production managers to control their manufacturing systems in terms of flexibility, reliability to production planning and labor cost. Design/methodology/approach - The complexity level of tasks will be analyzed based on the structuralist concept. Using the structure of task, the factors that significantly affect the task complexity in an assembly line will be defined, and the complexity level of the task will be evaluated by measuring the number of task components. Using the proportional 2-tuples linguistic values, the difference between the complexity levels of tasks can be compared and described clearly. Findings - Based on the structure of the task, three contributory factors including input factors, process-operation factors and output factors that significantly affect the task complexity in an assembly line are identified in the present study. The complexity level of the task is quantified through analyzing the details of the three factors according to two criteria and six sub-criteria within the textile case study. Originality/value - The proposed approach provides a new insight about the factors that have an effect on the complexity of tasks in production and remedies some of limitations of previous methods. The combination of experts' experience and scientific knowledge will improve the accuracy in determining the complexity level of tasks.

Keywords: Task complexity; AHP method; Linguistic variables; Proportional 2-tuple linguistic representation model (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eme:ijppmp:ijppm-12-2021-0705

DOI: 10.1108/IJPPM-12-2021-0705

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