Engineering and R&D maintain a repository of product specifications including manufacturing, supplier, performance, and service requirements that determine product quality. These product specifications are rarely evaluated against actual data, especially as it relates to market demand, process capabilities, supply disruptions, and service execution.
Goals and Objectives
Offer visibility into product sales, manufacturing, supply chain, inspection, in-service operations, and service execution to ensure better alignment of product design and quality standards to customer expectations. Provide data-driven decision support to maximize customer satisfaction against time, cost, and quality requirements for product development, manufacturing, and support.
Hardware: Servers, storage, IoT, mobile devices, and robotics
Software: Cloud, CAD, PLM, ERP, MES, SLM, BDA, cognitive/AI, and security
Services: Business services and IT services
Use Case Summary
Integrating available IoT data with a product specification and performance database can expose problems and trends before escalation and implement automated corrective actions or escalation to maintain acceptable quality levels. Intelligence and analysis of manufacturing execution quality as well as supplier performance and execution are available within PLM, and there is an open line of feedback from production, supply chain, in-service products, and field service to R&D and engineering.