Operational Performance Evaluation Model for Food Processing Machinery Industry Chain
This study aims to create a performance evaluation model for the food processing machinery industry. The goal is to help food processing plants improve both process quality and competitiveness. Additionally, component failures may disrupt the continuous operation of the food processing machine, potentially resulting in insufficient production and delays in delivery, which in turn leads to cost losses. For the sold food processing machinery, decreases in the average number of failures within a unit of time, the average repair response time when a failure occurs, and the average repair duration are three crucial factors in minimizing the total expected loss due to machine failures. Based on these three important factors, this study established the following evaluation indices: (1) the processing performance index, (2) the repair reporting performance index, and (3) the maintenance performance index. These indices serve as tools for assessing the performance of the three key operational aspects. This study employed a radar chart to construct the evaluation model, which can directly compare the critical values with the point estimates of three indices. Consequently, this approach can judge whether the operational performance has achieved the required level. This can maintain the simplicity and usability of point estimates while reducing the risk of misjudgment due to sampling errors.
Authors
- Huiqi Zhang (ORCID: https://orcid.org/0000-0001-8430-691X)
- Qiansha Zhang
- Chun-Min Yu (ORCID: https://orcid.org/0000-0003-2410-3023)
- Kuen‐Suan Chen (ORCID: https://orcid.org/0000-0002-1091-6392)
- Wei Lo
Institutions
- Chaoyang University of Technology (TW)
- Asia University (TW)
- Guangxi University of Finance and Economics (CN)
- Beijing Jiaotong University (CN)
- National Chin-Yi University of Technology (TW)
Publication Details
- Journal
- Mathematics
- Published
- 2024-10-26
- DOI
- https://doi.org/10.3390/math12213361
- Primary Topic
- Quality and Supply Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China