Issues, challenges, models and tools for the design, management and control of job-shop manufacturing system in food industry

The food processing industry is growing with retailing and catering supply chains. Efficiency, safety, quality, service level and, sustainability are key objectives in both food production and distribution systems. In particular, with the raising complexity of food product to match consumers requirements and food habits, the food production system are progressively shifting from processing line to processing job-shops as complex manufacturing systems in presence of multiple items (i.e., food, toppings, dressings, ingredients), resources and machines, and complex working cycles. Generic working cycle is realized across multiple tasks (i.e., operations), carried out by different human or automatic resources in multiple working stations. These systems present several storage and buffering areas and many assembly tasks, which are critical for perishable products sensible to environmental and physical stresses. Logistic efficiency, cost reduction, food quality, food safety are then key goals in managing the food production system. The design and control of food job-shop production system involves long and mid-terms strategic decisions (1), e.g., the plant layout, the number of machines or working stations, mid and short terms tactical decisions (2), e.g., the planning of ingredients purchasing, the production planning, and operational decisions (3), e.g., the tasks scheduling constrained by capacities, priority, working cycle precedence, safety limitations. The aim of the planners is to fulfill the food demand and the service level minimizing the production and logistic costs,, the environmental impacts,, by controlling the residual shelf life and the product quality and safety . This study presents an original conceptual framework for the integrated design, management and control of a job-shop production system in food industry. The framework is based on the development and application of different modelling and solving approaches and techniques. In particular, a simulation based supporting decision model is proposed. A case study from an Italian food catering company is also illustrated.