Digital twin-driven real-time planning, monitoring, and controlling in food supply chains

There needs to be more clarity about when and how the digital twin approach could benefit the food supply chains. In this study, we develop and solve an integrated problem of procurement, production, and distribution strategies (PPDs) in a medium-scale food processing company. Using the digital twin approach, the model considers the industrial symbiosis opportunities between the supplier, manufacturer, and customer using interval and sequence variables operating in a constrained environment using mixed-integer linear programming (MILP) and agent-based simulation (ABS) methodology. The study optimizes the make-span and lead time, simultaneously achieving a higher level of digitalization. The analysis demonstrates how digital twin accelerates supply chain productivity by improving makespan time, data redundancy (DR), optimal scheduling plan (OSP), overall operations effectiveness (OOE), overall equipment effectiveness (OEE), and capacity utilization. Our findings provide compelling evidence that the seamless integration PPDs enormously enhance production flexibility, resulting in an excellent service level of 94 %. Managers leverage real-time simulation to accurately estimate the replenishment point with minimal lead time, ensuring optimized operations. Furthermore, our results demonstrate that implementing PPDs has yielded considerable benefits. Specifically, we observed a remarkable 65 % utilization of the pasteurizer and aging vessel and an impressive 97 % utilization of the freezer. Moreover, by applying the DT model, the present model found a notable 6 % reduction in backlog, further streamlining operations and enhancing efficiency

Supply chain planning in the food industry : a systematic literature review

PURPOSE: Advanced Planning Systems (APS) can contribute to improved decision making and enhanced efficiency along complex food supply chains. This paper presents a systematic literature review of supply chain planning (SCP) in the food industry. In particular, the literature on three increasingly important planning tasks supported by APS is examined, namely Supply Chain Network Design, Sales & Operations Planning and Production Planning & Scheduling. METHODOLOGY: A literature review is conducted by systematically collecting the existing literature published between 1998 and 2020 and classifying it based on three planning tasks supported by APS modules (Supply Chain Network Design, Sales & Operations Planning and Production Planning & Scheduling). Furthermore, research papers are categorized according to the product under consideration, geographic region and method. FINDINGS: Multiple models for SCP practices have been developed. The modelling literature is fragmented around specific challenges faced in food supply chains. Empirical literature including case studies on the implementation of APS is sparse. The findings suggest that developed models for the three examined planning tasks are only implemented to a limited extent in practice. ORIGINALITY: This paper focuses on three planning tasks that are of increasing relevance for the food industry. The literature review can help practitioners within the food industry to get insights regarding the opportunities offered by the three software modules examined in this paper. Further research should be conducted in these areas to make literature on SCP more practically relevant for managers

Optimal batch scheduling of a multiproduct dairy process using a combined optimization/constraint programming approach

This paper presents the optimal batch scheduling of a multi-product dairy process using an approach that combines optimization and constraint programming techniques. A suitable model describing the subprocesses and production rules is developed allowing to obtain scheduling constraints relating the production process and the machines available together with their relative efficiencies. After the scheduling problem has been formulated, the batch scheduling of a real powder milk/yogurt process is obtained in an optimal manner using the proposed approach with the objective of meeting customers’ deadlines considering the efficiencies/costs of available alternative machines. Results using real consumer orders on some representative scenarios corresponding to the dairy production plant used as a case study are provided. This application shows a formulation closer to the engineering problem description thanks to the constraint-based language that facilitates the adaptation of the optimization objectives and constraints to real applications.Peer ReviewedPostprint (author's final draft

Generic modelling and simulation of operations and stock levels in supply chains

Imperial Users onl