Determining Factors for Minimizing Oven Downtime through Controlled Batch Management: A Multineutrosophic Approach with ARAS

Authors

Shakila Devi GT, Saveetha College of Engineering, Saveetha Institute of Medical and Technical Sciences, India.Follow
Sangeetha S, Saveetha College of Engineering, Saveetha Institute of Medical and Technical Sciences, India.Follow
Maikel Yelandi Leyva Vazquez, Saveetha College of Engineering, Saveetha Institute of Medical and Technical Sciences, India.Follow

Abstract

This study addresses a critical operational challenge in the baking industry: minimizing oven downtime through effective batch processing control. This study assesses which factors are the most critical contributors to minimizing downtime on batch processing operations to hypothesize efficiencies. But why is this problem? Sadly, much research has been done and found that ineffective resource allocation not only wastes funds but also increases carbon footprint for unnecessary baking, which is ironic since fresh products must drive demand at a low-cost. Furthermore, minimizing downtime allows for the more sustainability-oriented production that today's manufacturers are on the hook for. Therefore, testing new industrial process solutions is warranted. Currently, a lot of scholarly research exists about queuing theory and supply chain feasibility; however, little is known. Many investigations fail to concentrate on baking process optimization with uncertainty and subjectivity of decision-makers as top determinations. Therefore, this study is the first to bridge the gap using multineutrosophic theory and a decision-making tool called Additive Ratio Assessment (ARAS)—a prioritizing assessment tool—which provides nuance to criterion assessments and weighting via incremental rounds with experts rendered neutrosophic. Ultimately the neutrosophic composite-fueled determination of the most critical criteria/test variables includes: batch arrival rate, acceptable batch size and setup time. Ultimately regulating batch processing according to predetermined thresholds vetted against neutrosophic variables decreases downtime significantly without negatively impacting quality control. This project adds to the literature a new methodology that legitimizes ideation for uncertainty-based decision making along with new recommendations for implementation that reduce energy expenditure, new resource allocation and production efficiency takeaways for bakeries that improve their competitive advantage and sustainable quality of life.

Recommended Citation

GT, Shakila Devi; Sangeetha S; and Maikel Yelandi Leyva Vazquez. "Determining Factors for Minimizing Oven Downtime through Controlled Batch Management: A Multineutrosophic Approach with ARAS." Neutrosophic Sets and Systems 89, 1 (2025). https://digitalrepository.unm.edu/nss_journal/vol89/iss1/15