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All Journal Proceeding of The International Conference on Management, Entrepreneurship, and Business
Putri Ana Nurani
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Decision Sciences, Operations Research & Management

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Analysis of Production Capacity Planning Using Rough Cut Capacity Planning (RCCP) Method in the Manufacturing of Cleaning Tools (Case Study at CV Berkah Jaya Klaten) Dimas Eris Mahfud; Jemadi Jemadi; Putri Ana Nurani
Proceeding of the International Conference on Management, Entrepreneurship, and Business Vol. 1 No. 1 (2024): June : Proceeding of the International Conference on Management, Entrepreneursh
Publisher : Asosiasi Riset Ilmu Manajemen Kewirausahaan dan Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/icmeb.v1i1.133

Abstract

Amidst the growing competition in the industry, CV Berkah Jaya Klaten faces challenges in planning the production capacity of cleaning tools to meet market demand. This study aims to provide solutions to production capacity planning issues by applying the Rough Cut Capacity Planning (RCCP) method using the Capacity Planning Using Overall Factors (CPOF) technique and a system simulation approach. The planning process begins with demand forecasting using IBM SPSS Statistics 25 software, which produces the smallest Mean Absolute Percentage Error (MAPE) value using the Simple Seasonal method. These forecasting results are used to determine the Master Production Schedule (MPS). Processing RCCP data with the CPOF method requires MPS data, processing time for each workstation, and historical proportions calculated from standardized processing times. The system simulation of production capacity planning is conducted to model real conditions and evaluate various production scenarios. The simulation results reveal that the required production time capacity each month always exceeds the available time capacity, indicating the need for capacity adjustments to avoid bottlenecks and improve efficiency. With this approach, CV Berkah Jaya Klaten can plan production capacity more efficiently and effectively, ensuring product availability in accordance with customer demand.
Co-Authors Dimas Eris Mahfud Jemadi Jemadi