OMAC Publishes Data Governance Guide in Collaboration with ei3
As cloud-based analytics and digital transformation evolve, creating the foundation of the “data-driven” world, manufacturing organizations are scrambling to implement suitable data governance policies. OMAC’s latest initiative, led by ei3‘s Mark Fondl, establishes a framework and guidelines to protect precious proprietary information while enabling secure data sharing.
The result of the initiative was The Practical Considerations for Data Governance guide, which offers a real-world approach to segmenting, sharing and securing plant floor data. It covers the complete data lifecycle from creating a common data dictionary, identifying data sources and applications, stakeholders, storage, compliance, and recommended data governance best practices.
About the Data Governance Workgroup
The workgroup brings together a vibrant automation ecosystem with individuals from around the world representing end users, machine builders, system integrators and technology vendors. Participating organizations include:
- Leading Manufacturing Companies such as Cargill, Pepsico, and Corning
- Global OEMs including Mettler-Toledo, Milacron, Barry-Wehmiller, and Nordson
- System Integrators like Rovisys, Martin CSI, and Applied Control Engineering
- Groundbreaking Technology Companies like ei3 Corporation, Siemens, General Electric, Rockwell, Cisco, Mitsubishi Electric Europe B.V. , and
- Industry Associations like the PMMI amongst others
An Introduction to Data Governance
Creating a Common Data Dictionary and Language
Types and Sources of Data in Manufacturing
Applications that Utilize Plant Floor Data
Individuals, Organizations, and Companies that Use the Data
Key Components of Plant Floor Data
Organizations and Standards to Consider for Data Governance
Data Storage and Compliance
The Potential of Data Governance
Plant floor data is one of the most important sources of data that creates information required to operate both production and business systems. Communication and computational technologies are improving data access and allowing tighter integration with a variety of applications throughout an enterprise. It is thus vitally important for companies to create a Data Governance policy that identifies, organizes, and coordinates data usage.
The steps listed in this document should provide guidance on the various steps required to best utilize the data being generated in the automation machines and process systems in the plant. Today it is not uncommon for individuals to use data without fully understanding the data, how it’s collected or how it relates to products. A data governance plan or policy will resolve these issues and unleash the potential stored in data while protecting from their inappropriate usage.
Like any data, plant floor data can be interpreted in many ways; each group of users, be it operators, service technicians, or managers, will find their own individual path to generate value of that data as it pertains to their job function. Data scientists can tremendously help to unlock the full potential contained in the huge quantities of data generated and/or handled on the shop floor.