Research on Performance of Multi-Skilled Workers for Sustainable Production Planning In Seru Production Systems
T. Venkata Deepthi1, K. Ramakotaiah2, K. Krishnaveni3

1T.Venkata Deepthi, Department of Mechanical Engineering, K L E F, Vaddeswaram, India.
2K. Ramakotaiah,, Department of Mechanical Engineering, KKR&KSR Institute of Technology and sciences, Guntur, India
3K.Krishnaveni, Department of Mechanical Engineering, KKR&KSR Institute of Technology and sciences, Guntur, India

Manuscript received on 04 July 2019 | Revised Manuscript received on 08 July 2019 | Manuscript published on 30 August 2019 | PP: 1016-1028 | Volume-8 Issue-10, August 2019 | Retrieval Number: J91720881019/2019©BEIESP | DOI: 10.35940/ijitee.J9172.0881019
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Abstract: A Thriving demand of manufacturing industries causes the escalation in carbon emission and worsening the environmental conditions, to ameliorate such scenario sustainable development has attracted by countries policy makers, academia, manufacturing industry, and service industry. The primary consumers of energy i.e., production systems are the major contributors of carbon emissions and to mitigate environmental hazards sustainability factors taking part in their concerns. This paper investigates the benefits of switching to Seru production system (Cell manufacturing system) in terms of both the economic and ecological performance. A mathematical model was developed with the objectives of minimizing the total training cost of the workers which in turn will decrease the processing time and energy utilization leading to control the carbon footprint of the company. The effective scheduling of skillful workers to serus ensures the significant result on achieving the goals of the model, for this a two-stage heuristic and modified moth flame algorithm are deployed. The proposed model yields a set of alternative Pareto optimal solutions with the minimal carbon footprint on several numerical instances. The computed results will garner a sustainable manufacturing system and assure the efficacy of the suggested algorithm.
Keywords: Seru system; sustainable manufacturing; ecological; training cost; Heuristic algorithm.
Scope of the Article: Advanced Manufacturing Technologies