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A Manufacturing Cost Estimation by Utilizing a Novel Sensor Based Cost Model in a Knowledge Management System

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Advances in Manufacturing Processes, Intelligent Methods and Systems in Production Engineering (GCMM 2021)

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Abstract

Nowadays, many small or medium size manufacturing companies are struggling to identify the right solution to tackle the problems of long production cycle time, poor quality and expensive cost in their manufacturing processes. An attractive method to solve these problems is to introduce knowledge management system in their processes. However, most available knowledge management systems are not feasible for them, as they are either too expensive or lack of necessary functions to fit their specific requirements. In order to generate a flexible and effective knowledge management system for small or medium size manufacturing companies, it is important to facilitate suitable sensors to observe and monitor manufacturing processes in a company, so that the efficiency of the manufacturing processes can be assessed in real time and the cost of the manufacturing processes can be calculated accurately. In this research, the manufacturing processes are observed via a power meter that is assembled on the machine. The efficiency measurement and calculation of the manufacturing processes are gathered in a knowledge management system database that is created by utilising Microsoft Access Software. One of the key beneficial feature of the database is the calculation of the annual manufacturing cost taking account of the real utilization rate of the machines. In this paper, how the real utilisation rate is monitored and integrated into general cost model is presented together with the application cases of two industry companies.

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Correspondence to Xun Chen .

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Tokucoglu, H., Chen, X., El Rhalibi, A., Opoz, T.T. (2022). A Manufacturing Cost Estimation by Utilizing a Novel Sensor Based Cost Model in a Knowledge Management System. In: Batako, A., Burduk, A., Karyono, K., Chen, X., Wyczółkowski, R. (eds) Advances in Manufacturing Processes, Intelligent Methods and Systems in Production Engineering. GCMM 2021. Lecture Notes in Networks and Systems, vol 335. Springer, Cham. https://doi.org/10.1007/978-3-030-90532-3_50

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