An expert system to minimize operational costs in mixed-model sequencing problems with activity factor
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One of the major issues in industrial environments is currently maximizing productivity while reducing manufacturing cost. This can be seen clearly reflected in mixed-model assembly lines based systems, where obtaining efficient manufacturing sequences is a key to be competitive in a dynamic and globalized market. However, this continuous cost reduction and productivity growth should not penalize the welfare of employees. This work is intended to address this lack of compatibility between the economic and social objectives through the study of the mixed-model sequencing problem from both the business and labor perspective. This is done by considering the possibility of reducing or increasing processing times of operations by varying the work pace of line's operators within the permissible legal boundaries. Thus, depending on this flexible activation time of operators, the amount of completed work and idle time will be one or the other and, consequently, the productivity of the line will also improve or get worse. In this regard, we propose new approach to the sequencing problem without incurring cost increases and providing a safe working environment, in accordance with applicable law. This new approach leads to obtain efficient manufacturing sequences, in terms of both productivity and labor conditions. Specifically, the objective of the new problem is minimizing the unproductive costs of the line by incorporating the possibility of increasing production through the variation of the work pace of line's operators. Increasing the work pace of operators, the amount of non-completed work or the preventable idle time can be reduced and therefore, their associated costs too. In addition, and without losing sight of the effort involved in working with a work pace above the normal, we propose several economic criteria to compensate the activation of workers where necessary
CitationBautista, J., Alfaro, R. An expert system to minimize operational costs in mixed-model sequencing problems with activity factor. "Expert systems with applications", 15 Agost 2018, vol. 104, núm. 2018, p. 185-201.