This is my second part of the series related to SMAC influence. In this I will be focusing on Business Analytics and Intelligence as one cannot really expect to improve manufacturing performance unless you can measure at least some of the key variables impacting performance.
Analytics was part of shop floor solutions from the beginning but in various forms. With the revolution in technology, the way critical information is presented in relation to other items makes analytical solutions far more effective. Real time information, critical decision making data in finger tips, analytical models that help in predictive analysis have become a reality. The SPC solutions which are part of analytical solutions also serves as the primary resource for identifying areas of improvement and eliminating quality issues within the production environment. As a result, one can drive greater consistency within the manufacturing operations and enhance the productivity and profitability of a company.
Several Key Performance Indicators (KPIs) that are used in shop floor systems are Line View to check the utilization, Tool or Equipment Performance, Feeder Performance, Overall Equipment Effectiveness(OEE), 1st Pass Yield, Performance to Schedule (On time shipments vs. all shipments), the Rate of successful NPI. But these KPIs are not sufficient for decisive decision making. It is also crucial to be able see the impact of specific machine ID, operator (tester) ID, tool used and feeder used and vendor materials used on any KPI which indicate a poor or declining performance. Earlier days it was difficult to get all the related data together and present them as useful information.
The good news is that the shop floor is more “intelligent” than it has ever been. Devices such as RFID, remote sensors, real-time location systems (RTLS) and use of wireless networks, hand held devices have created sophisticated shop floor networks. The reporting tools have also become sophisticated to show the information in an effective way. One can slice and dice the information in various ways using these tools with not much technical help. Business intelligence in the manufacturing companies nowadays is capable of real-time visibility through automatic data capture from the shop floor. It provides analytics on KPIs to optimize business performance and enables a real-time collaborative enterprise (from other business units to supply chain partners).
Business Intelligence and Analytics at shop floor is only part of the bigger picture. Supplier Intelligence /Analytics along with inter factory information within the enterprise completes the equation. Real-time data is useful for real-time management. Predictive data is useful for managing company’s strategies and objectives. Hence there is demand for forecasting software applications and what-if scheduling in ERP and MES applications. Forecasting and predictive analytics are no longer specialty applications with nice-to-know information. Real-time manufacturing intelligence enables a company to manage using realistic what-if projections running weeks or months down the road. A general architecture diagram is shown below.
General Architecture Diagram
Intra-Enterprise Collaboration is the happening thing now. The classic “four-wall operation” is on the decline. Even a self-contained company may have multi-site and global operations, thus involves an extended supply chain in and of itself. Having a good, effective Business Intelligence and Analytical system is key to the success of any manufacturing company.
Conclusion:
In the past because of various reasons like Internet connectivity, non-availability of lower-cost automated data collection systems, poor Work-In-Process visibility hampered business.
Trusted data result in better decision making and increase the ability to be more responsive to the market and the environment. Analytics provide manufacturers with a basis to evaluate and optimize business processes. Further applying business intelligence and operational analytics to real-time shop floor metrics transforms reactive processes into predictive and proactive manufacturing operations.
On-time delivery can only be achieved through accurate production forecasting and process visibility based on real-time shop floor information combined with early warning systems and exception reporting. Until now, monitoring supply chains was an expensive process, and largely ideal.
Together, real-time trusted data, process visibility and analytics bring cost containment, production improvement and revenue growth. We now have the ability to monitor supply chains, distribution methods and WIP not just monthly or weekly, but real-time, remotely, round the clock, and weeks and months ahead.
References:
- Various Internet and Other Sources.
Sudheer 