Optimizing the clinker production by using an automation model in raw material feed

Authors

  • Ahmad Hidayat Sutawijaya Universitas Mercu Buana
  • Abdul Kayi Universitas Mercu Buana

DOI:

https://doi.org/10.12928/ijio.v2i1.3002

Keywords:

Automation process, Clinker production, Root Cause Analysis, CPPS, Raw Mill

Abstract

The clinker production process involves much equipment and material flow; thus, an operating system is needed to regulate and manage the production process. XYZ company uses an operating system for clinker production called Cement Management Quality (CMQ). The CMQ operation on clinker production is considered semi-automatic because it requires many interventions from the operator. Furthermore, the program is limited under specific condition. As a result, the quality of the clinker is decreased, and the energy consumption is increased. The failure of clinker production is related to the CMQ system, and it is vital to solving the problem appropriately. Since the CMQ system is connected with many aspects, it is essential to find the root cause. Root Cause Analysis (RCA) method is suitable to find the root of the problem for a complex system. After researching using RCA, the main problems on the CMQ system is the data not appropriately integrated, and the process algorithm is insufficient. The new integration of data transfer and new algorithms are developed as an attempt to solve the issues. The new data integration model and algorithm are applied through the simulation method as a test case before taking complete corrective action on the CMQ system. The new model's application shows the standard deviation of the process is decreased under the specified threshold. The method provides good results for improving the quality of the clinker production process. It can be used as an essential reference for applying the automation model in the clinker production process.

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Published

2021-02-24

How to Cite

Sutawijaya, A. H., & Kayi, A. (2021). Optimizing the clinker production by using an automation model in raw material feed. International Journal of Industrial Optimization, 2(1), 17–32. https://doi.org/10.12928/ijio.v2i1.3002

Issue

Vol. 2 No. 1 (2021)

Section

Articles

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