Despite challenging supply chain situations, manufacturers are making progress toward Industry 4.0. Most understand that artificial intelligence (AI) and improved analytics can lead to better decisions and, thus, business benefits. However, creating the data management structure for success is something many are still learning. Research shows how top performing companies are making more significant strides than others. In short, they understand, invest in, and make the most of many aspects of people, process, and technology. Together, they enable capabilities that close the loop from data to information to insights to decisions and to profitable, timely action.
A free downloadable Tech-Clarity eBook ‘Manufacturing in the Age of AI: Progress and Expectations’, based on over 300 responses from manufacturers in various industry segments addresses crucial subjects when enabling AI with manufacturing data.
Industry 4.0 Vision
The future of manufacturing is more flexible, agile, and responsive based on AI and intelligent automation. This is the vision of Industry 4.0, which goes by many other names. While the concept encompasses the entire enterprise and supply chain, the manufacturing area often poses the most significant challenges and opportunities for gaining substantial benefits.
Closing the Loop from Data to Action
For those who have yet to become versed in the challenges and nuances of manufacturing data management, a recently published white paper provides a visual about data management for closing the loop. It explains the elements of a consistent manufacturing data management system at a conceptual level.
Establishing consistent and complete manufacturing data management is multi-faceted. Ideally, information flows from its origin to storage, harmonization, enrichment, through analysis for decision-making, and into applications for action. Closing the loop from data to action – is genuinely complex.
The Reality: Gaps in Data Flow
In reality, most companies have gaps in their data flow. In the recent survey, only 5% report not having manual handoffs at any of the seven points we listed. More than half of the manufacturers in this sample report a gap in the data flow at analyzing data from various sources. This may be top of mind as companies embark on advanced analytics and big data projects. Gaps exist for many at every stage, from moving OT data into a format for IT use to creating context, generating insights, making decisions, and taking appropriate action.
Why Manufacturing Data Management?
Companies are discovering that making progress on Industry 4.0 and gaining its benefits rests on mastering manufacturing data management. Getting beyond data to information, intelligence, and actionable insights requires all aspects of data management. Ideally, this is a unified, consistent approach that supports the manufacturing operation – and the business.
Broad Business Benefits
We asked to understand what benefits companies are getting or expecting from better and more unified manufacturing data management. The question was: “Which benefits do you see or would you expect from better and more unified plant data management that offers OT and IT data in context, ready to analyze and act on?” Respondents could select all that apply. Responses were divergent, with only two chosen by more than half of respondents: increased product quality and faster, more reliable response to exceptions.
Foundation for AI and Analytics
Anyone who has attempted an AI or advanced analytics project knows sound data management is a prerequisite. If any aspects of manufacturing data management are weak, it can limit the success of analytics and AI efforts. Analytics can be used to gain insights into any of the improvement areas listed.
For more information: www.criticalmanufacturing.com