This module introduces and explains the various types of MOM solutions and their roles in the manufacturing operations systems landscape. Connectivity and integration between all manufacturing, business applications and more is increasingly important when facing the current challenges. To achieve this requires an enterprise application framework or information architecture.
Architectures for Smart Manufacturing and Industry 4.0 receive special attention. We explain integration and communication standards, like OPC UA and MQTT. To be able to leverage the benefits of Smart Manufacturing and Industry 4.0, standardization and precisely defined processes and products are required. When first time right, efficiency and effectiveness are our goals, then we need to define and maintain our manufacturing master data carefully.

Obvious, you would say. But too often, master data are completely forgotten or only partially taken into account at best.
Not only for new product development and introductions it is important to define how a product looks like and how it must be put together. It is crucial for any product, process at any stage to be successful as a manufacturer. To maintain standardized and well-structured processes for manufacturing master data, supported by the right tools, is an excellent starting point.

  • Describe the roles of the various MOM solutions
  • Explain the mapping of MOM solutions to the ISA-95 activity models
  • Identify the differences between the presented integration approaches
  • Describe the elements of Smart Manufacturing architectures
  • Explain the importance of Manufacturing Master Data.
  • Describe the role of PLM and NPDI and recognize their benefits.
  • Explain the importance of master data governance and ownership.
  • What are MOM Solutions?
    • MES, LIMS, CMMS, APS, WMS, etc.
    • Examples
  • Solution Architecture
    • Integration Architecture
    • Solutions and ISA-95 Models
  • Architecture for Smart Manufacturing
    • RAMI4.0, Edge, 3 Tier, etc.
  • Manufacturing Master data
  • PLM and NPDI
  • Governance: Organization and Ownership
  • Conclusions and Wrap-up