Smart Containers—Enabler for More Sustainability in Food Industries?

In recent years, Machine Learning (ML) applications for manufacturing have reached a high degree of maturity and deal as a suitable tool for improving production performance. In addition, ML applications can be used in many other areas of production to enhance sustainability within the manufacturing process. One specific area is the storage and transportation of bulk materials with Intermediate Bulk Containers (IBC). These IBCs are currently used solely for their primary purpose of storage and transportation for raw and finished goods. But for a major part of their handling cycle time these IBCs are a black box, and therefore do not add additional value to manufacturers. By equipping those containers with sensor technology, new data can be generated along the entire supply chain, taking the sustainability of production to a new level. Within the research project smart.CONSERVE we use this additional data to prevent waste of resources through storage of production goods in defective IBCs through predictive maintenance. In this publication, we describe how the use of such smart IBCs in the food industry increases supply chain visibility and reduces food waste by presenting a number of use cases that are possible due to the new data availabilities. Additionally, we provide insights into the transferability of these use cases to other industries and the many opportunities for manufacturers to develop new smart services and ML applications based on the collected data to increase sustainability.