A data model for collaborative manufacturing environments

Abstract

[EN] This paper addresses the problem of information exchange required for collaborative manufacturing planning processes at supply network levels. For a few years now, the traditional manufacturing planning paradigm has shifted toward optimizing collaborative plans at the inter-enterprise level driven by cloud-enabled tools (manufacturing platforms), from which the need to share data between networked partners arises to solve intra-enterprise plans in real-time scenarios. Collaboration among enterprises has to increasingly deal with the sharing the information encoded in ontologies. Cloud repositories are seen as collaboration mechanisms whose main aim is to exchange data regardless of their origins and nature. In line with this, industrial planning research is encouraged by solving problems regarding information exchange, sharing and storage in cloud collaborative environments. The contribution of this research paper lies in identifying information used by manufacturing enterprises when they follow their planning processes in a cloud collaborative manufacturing context to propose common formalized data terminologies. This paper introduces a novel data model for collaborative manufacturing environments (CMData) by building a taxonomy of data concepts to represent information about the replenishment, production and delivery planning domains. Although there are standards aimed at exchanging product data that covers different parts of the history of a product from conceptual design to disposal, this proposal is defined as a detailed version of such current standard initiatives covering the specific area in the domain of production planning and supply chain collaboration. Moreover, this proposal complements and gives an answer to the new cloud collaborative business needs from industry. The CMData has the following objectives: (i) to solve problems related with data interpretation; (ii) to solve the sharing between enterprise legacy systems and cloud environments through the mapping procedure and (iii) to identify the required data coming from different enterprises to collaboratively compute the joint planning activities. The proposed CMData are validated through their application in the collaborative production scheduling plan of a second-tier supplier and a first-tier supplier in the automotive industry. Future work and open issues are also discussed. (C) 2021 Elsevier B.V. All rights reserved. Keywords