Fuzzifying approach to special cutting in poultry meat production planning

ABSTRACT

In this study, a method for assigning jobs in the special cutting of chicken parts was developed. In the developed method, a deterministic mathematical model is used to simulate the assignment of jobs in production lines for 1 week, with the maximum revenue from the weekly production employed as an objective function. Compared with human judgment for assigning jobs, the average weekly revenue increased by 27.9%, the average weekly throughput increased by 25.1%, and the average weekly backorders decreased by 13.4%. In addition, a fuzzy mathematical model was developed to assign jobs under uncertain demand and production time. In this model, the planner could select the membership level of two fuzzy parameters. The flexibility of demand and production time increased as the fuzzy parameters decreased. The mathematical model produced better results as the flexibility of the fuzzy parameters increased. The fuzzy mathematical model yielded better overall results compared to the deterministic model under realistic situations.

Abbreviation: Deterministic mathematical model (DMM); Fuzzy mathematical model (FMM); Production planning (PP)

KEYWORDS:

• Deterministic model
• fuzzy mathematical model
• production planning

Compliance with ethical standards

The company considered as the case study provided data and the company allocation plan for comparison with the proposed approach. We, the authors, were under no pressure or competing interests that affected our professional judgment in any manner. The results of the research are ours alone, without conflict of interest. This work does not comprise any investigation involving animals or human participants.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This study was funded by Chiang Mai University through the Excellence Center in Logistics and Supply Chain Management.

Notes on contributors

Komgrit Leksakul

Komgrit Leksakul is a senior lecturer in Industrial Engineering, Chiang Mai University, Thailand. He received his D.Eng degree from the Asian Institute of Technology, Thailand (Industrial Engineering), Thailand in 2005. His D.Eng studies mainly focused on Advance Optimization. Currently, he is involved in plasma, MEMs, and developing microfluidic system for lab-on-a-chip device.

Chanchai Apiromchaiyakul

Chanchai Apiromchaiyakul is manager of innovative business development department at Science and Technology Park, Chiang Mai University. He received Master degree in Industrial Engineering from Chiang Mai University in 2011. His research interests include applications of mathematical modeling for optimization, decision making and management.