Effective Capacity Planning for Operations in a Contract Manufacturing Setting

Document Type

Article

Publication Title

Proceedings of the International Conference on Industrial Engineering and Operations Management

Abstract

Capacity planning is one of the most challenging yet important activities for manufacturing companies. Several different forms or resources are required for operation, including both humans and equipment. Each of these resources has a finite capacity and must be allocated to address various projects. Spikes and lulls in resource usage result in inefficiencies, timeline delays, and reduced profitability. Understanding a manufacturing company’s resource capacities, planning their upcoming work, and strategically allocating those resources are essential for optimizing its production. This becomes an even more daunting task in a contract manufacturing setting because the company is reactionary to its customers’ placement of orders. It is rare to foresee the exact amount of incoming work, so how can contract manufactures improve their capacity planning to avoid drastic lulls and spikes in resource utilization? Customers may provide a demand forecast to the manufacturer, but this is not frequently available. The manufacturer may also attempt to draw insight from customer order patterns, but this can only usually be attempted on a few high-order products. Multiple departments must be involved and provide input into forecasting, and the results affect multiple departments as well. However forecasting is accomplished, this expected workload must be systematically added to existing workload to understand the best way to allocate resources, take on or refuse new projects, and invest in resource capacity expansion. This paper aims to advise contract manufacturers on methods and metrics to effectively level-load their shops and increase their productivity levels.

DOI

10.46254/an13.20230011

Publication Date

3-9-2023

Comments

Presented at the 13th Annual International Conference on Industrial Engineering and Operations Management.

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