antek Systems Inc. provides CAD, CAM, MES and ERP software solutions for the sheet metal and structural steel industry. Anupam Chakrabory, commercial director, talks with FFJournal about optimizing manufacturing processes with cloud-based technologies, AI and machine learning.

Traditionally, there has been a gap between processes—estimation, engineering and fabrication. This gap was the result of the inability to access machine data in real time, and it often led to lower visibility of key performance indicators (KPIs) to management.

The evolution of sensors, instruments and devices interconnected with computers has bridged the gap, providing much better control and visibility of multiple processes. The adaptation of cloud-based technology along with AI and machine learning has largely contributed to converging, coordinating and controlling the various processes, along with developing mechanisms to provide real-time feedback for improvements.

ERP is a business management software system that spans many different business processes. MES works in conjunction with an ERP system to provide better control and visibility of the manufacturing process, along with other peripheral processes, such as design and engineering.

An MES system connects ERP with the various facets of manufacturing. It provides real-time visualization on important KPIs, like OEE, capacity utilization and productivity. With AI and machine learning technologies, along with big-data analytics, MES can also provide real-time feedback on activities that can improve process parameters.

Before implementing an MES, every company should ask itself what it has, what it doesn’t and identify gaps.

MES connects the ERP and shop floor to create a real-time and accurate stream of data which, when combined with the right analytics platform, gives great visibility of the manufacturing operation. At the same time, the feedback loop updates parameters that are based on individual shop floor conditions, which creates a more advanced MES.