Manufacturing Intelligence

Enterprise Manufacturing Intelligence integrates, connects and unifies data sources such as Manufacturing Execution System (MES), Quality Management System (QMS), Advanced Planning and Scheduling (APS), Laboratory Information Management System (LIMS), Enterprise Resource Management (ERP) and others – into one accessible analytical data model providing capabilities to explore and drill down into contextualized data.

Enterprise Manufacturing Intelligence is used at the plant level to improve collaboration and data exchange between the shop floor and enterprise systems, and/or at the enterprise level to benchmark and compare production runs or predict various plant operations. As data from different sources are combined, they can be put into a new context and provide users with a different and more complete perspective of manufacturing operations regardless of where the data originated.

A worker looking on her tablet.

Simply put, manufacturing intelligence is the term that refers to the software systems that integrate your manufacturing operations data for deeper analytics. These systems rely on big data analytics compiled from IIoT and other technologies. While some may equate MI with Business Intelligence (BI), there is a difference – manufacturing has different needs and goals than a business front office. BI traditionally measures sales and revenues and other Key Performance Indicators that are of a corporate nature. MI measures the productivity of both humans and machines on the factory floor. It can plug into BI to add more value to the enterprise, but, by itself, it is an independent stream of insight into Manufacturing operations using tools that were hitherto in the IT domain.

For manufacturing, production is everything. It is ensuring that each machine on the production line is operating properly and manufacturing products to exact specifications. Each machine generates data regarding its production, but that data is meaningless if siloed. Through data analytics, MI can monitor the factory’s entire infrastructure, know what machines aren’t producing to the specificity and improve overall efficiency. Workers have access to this information in real time so issues can be addressed as they occur. It also produced historical data to track past performance and outcomes and compare them to current or future needs.

Computer technology on the factory floor is not new, so why does MI matter now? It is the modernization of analytics tooling for manufacturing data. It takes advantage of modern computing technologies like Big Data and makes them accessible to the factory floor both in real time and for enhanced outcomes using machine learning.