Abstract
Although the potential of Industry 4.0 has been widely discussed and demonstrated, manufacturers need appropriate approaches to navigate the opportunities enabled by emerging digital technologies. For most manufacturers, full system automation is not a feasible or realistic option. Instead, smaller, more focused use cases should be identified. Based on a case study with a manufacturer of traditional meat products, this study uses a framework for data-driven improvements to evaluate different digitalization use cases. The case company is currently exploring digitalization opportunities with the objective of enabling more data-driven decision-making, improving quality control and traceability, as well as enhancing production efficiency. Focusing on cured meat products, this context presents some unique challenges. This includes variability in raw materials, frequent production plan updates, a high level of craftsmanship, a product with attributes that are difficult to measure, and traceability requirements. Four different use cases are identified and evaluated, focusing on how the data are collected, shared, and analyzed, how it is used for optimization purposes, and how it provides feedback to the process. This study contributes to testing a framework for evaluating digitalization use cases. Moreover, it provides insights into how a tradition-based food manufacturer should navigate and prioritize digitalization initiatives.