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Cloud Computing Architecture for Manufacturing Data Management

Intense global competition has forced many US manufacturers to examine their current business practices as well as evaluate how to meet these challenges and remain competitive. Major emphasis has been placed on disruptive innovation and manufacturing research with recognition of the need for better Manufacturing Data Management (MDM), automation, continuous improvement, and process optimization through data mining. The benefits of effective MDM include reduced downtime, improved operator productivity, optimal machine scheduling, Overall Equipment Effectiveness (OEE), alarm/alert management, and better product quality. Conversely, small to medium manufacturers do not have the capital needed for data management technology and resources. In addition, these manufacturers are not able to justify the return on investment; plus they have to train personnel, maintain support staff, and manage upgrades and maintenance of the applications. In this paper, the implications of using the on-demand cost effective cloud computing philosophy for MDM are discussed. The dynamically scalable resources are externally hosted by a third-party and follow pay-per-use methodology with no software licensing, high service level agreements, and secured transactions. The cloud computing architecture has been developed as part of the supervisory system thrust area for the Smart Machine Platform Initiative (SMPI). The supervisory system is defined as a system that integrates and coordinates multiple process monitoring and control modules such that a globally optimal machining solution could be delivered real-time for desired quality and maximum productivity. The paper also features an in-depth discussion of the implementation architecture, benefits, case study, limitations, security concerns, and future work needed to ensure success of the cloud computing for effective manufacturing data management.

Reference: Cloud Computing Architecture for Manufacturing Data Management, Amit Deshpande (TechSolve), Kevin Bevan (GBI Cincinnati), Mark Doyle (I/Gear), 2010 Conference of the Society for Machinery Failure Prevention Technology (MFPT), April 13-15, 2010, Huntsville, AL.

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