Redistributing food manufacturing: models for the creation and operation of responsive and agile production networks

Abstract

The food industry is a mature industry where its profit margins are thin and its R&D failure rate for new products is substantial. Both facts indicate that decent return on development investment cannot be provided and that the food industry cannot still rely on its traditional way of thinking and innovating. New product development cycles should involve not only the product itself but also the entire manufacturing and distribution network. Hence, collaborative manufacturing and servitization models are key elements for the rapid transformation of the new food industry. Moreover, recent developments in technology have the potential to shift manufacturing production away from large scale manufacturing plants to a network of distributed, smaller scale localized and customizable manufacturing facilities. Such a network is the crucial enabler for the on-demand manufacture of new or even, existing food products to rapidly respond to the consumers´ demands.

Keywords:

• Food industry
• re-distributed manufacturing
• new makespaces
• production networks
• new product development

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work has been partially funded by UK Engineering and Physical Sciences Research Council (EPSRC) research grant with number EP/K014234/2. The authors fully acknowledge and thank EPSRC for the support.

Notes on contributors

Panagiotis Tsimiklis

Panagiotis Tsimiklis A proactive and assertive Manufacturing Engineer with a deep background in Industrial Operations, Packaging, Innovation and Project Management. Spent 20 years in industry, principally as a Senior Engineering Manager with a number of Food, Chemical and Service companies.

Charalampos Makatsoris

Charalampos (Harris) Makatsoris is Professor of Manufacturing Operations in the Sustainable Manufacturing Systems Centre at Cranfield University. He has extensive expertise in process engineering, manufacturing systems, operations and control. He is researching Distributed Artificial Intelligence in manufacturing with specific focus on responsiveness through lead time compression and resilience and continuity of manufacturing operations, specifically for the process and formulation industrial sectors. He is a Chartered Engineer, graduated Imperial College London with a Mechanical Engineering degree and a PhD in Manufacturing Systems. He also has experience in technology transfer through commercializing technology he has developed.