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Duality between OEE and Industry 4.0 is pushing operations to a new level

Dr Ravindra Ojha on how to move beyond the pilot stage and achieve scale with Industry 4.0

by Dr Ravindra Ojha, Professor - Operation, Great Lakes Institute of Management, Gurgaon
Industry 4.0: Tech-ing it Forward

Overall Equipment Effectiveness (OEE), computed as the product of three critical constituents – Availability (A), Performance(P) and Quality(Q) is considered a significant productivity metric of a manufacturing ecosystem. A perfect OEE score of 1 is delivered when each of the three constituents has a perfect score of 1. A perfect score in A would demand 100% availability (zero breakdowns) of the producing machines, an ideal score of 1 in P would mean output as per predefine perfect standards (zero performance losses) and finally, a perfect score in Q would mean six-sigma quality levels (zero quality defects) to the customer. The product of the three fractional constituents to arrive at the OEE sets up a challenging target for the manufacturer. An OEE index of 80% or more for the bottleneck asset remained to be a healthy index in the shop floor till the recent past. The same is being challenged now by the new age technology.

The growing need for variety in products leading to near single-piece flow and quick changeovers in shop floors, near perfect quality levels with high process capabilities, zero-breakdowns of machines using predictive analytics, remote/reduced human touch, driving to eliminate the eight process wastes of lean, progress made in the application of digital technology and the fierce competition today have pushed for the creation of smart factories in this world of Industry-4.0 (I4.0). With the advent of the technology-driven I4.0, the production shop floors of pharmaceutical, agri-food, IT, apparel, automotive, and FMCG industries are transforming quietly but effectively.

Smart factories’ costly machines and equipment today are expected to sweat continuously, in terms of delivery, from day one when they get commissioned. They need to ensure the value-added time in the process to significantly improve from 20% (normally) to 80% and more through the elements of I4.0 – Internet of things (IOT), Artificial intelligence & Machine language (AI&ML), Radio frequency identification (RFID), Cloud computing (CC), automation through robots and other digital initiatives. The large-scaled and mass-customized output has to be defect free (zero PPM & PPB) using optical scanners, AIML and big data analytics.              

In the new manufacturing ecosystem of I4.0, the tracking of operational productivity through OEE has become significantly easy, and conveniently available on a real-time basis. It has become more relevant for high-investment assets. Continuous improvement through benchmark target setting (best A, best P and best Q) of the three constituents is bound to provide a competitive culture in the smart factories.

Never has OEE been so important than today when the digitalization drive is galloping so briskly. Some reasons why the technology-enabled industry4.0 has been nudging a greater degree of OEE application in smart factories are

  • Unlike in past, when data collection and manual computation of OEE required effort and postmortem/reaction was the way of life, today, in the digital world, effort is negligible and data is available instantaneously for action in a more proactive approach.
  • The large number of sensors used in manufacturing processes in I4.0 provide better quality, more granular, real-time and more accurate data to act upon.
  • Integrating technology of IoT, RFID, sensors, AIML, robots/cobots and Cloud computing of I4.0 has pushed the need for OEE application for productivity measures.
  • The large data available through digital technology has greatly facilitated in predictive analytics of machine maintenance, optimization of the manufacturing processes and product life cycle improvement.

OEE is accelerating the manufacturing shop floor transformation by providing the appropriate impetus for implementing I4.0. The impact of OEE on I4.0 can be experienced in the following ways:

  • OEE is a comprehensive and powerful metric of manufacturing set up. Anything that can be measured will be done. Therefore, the big performance promises of I4.0 implementation can be best monitored by the trends of OEE. The new age industry is using it effectively today. 
  • High investment in the technology-driven assets of I4.0 is pushing focus on faster return on investment (ROI) and there is no better index to assess that than OEE.
  • The elements of OEE throw up useful benchmark indices and insights to the shop managers which serve as the continuous target to achieve (internal benchmarking).
  • OEE-related granular data of its three constituents from the process sensors throw up a lot of useful information for loss time analysis, process optimization and proactive alert generation to improve operational performance.

In conclusion, OEE has revived its presence to a different level in the current digital manufacturing world. Industry-4.0 will quickly take deeper roots in the industry to meet the competitive requirements and deliver the changing consumer volume, variety and velocity needs. OEE and I4.0 are inseparable and they aptly supplement each other to improve the shop floor performance. Furthermore, I4.0 has been facilitating in real-time data collection through high-tech devices to facilitate quick improvement actions proactively. This two-way (duality) relationship between OEE and I4.0 is taking manufacturing to another level of performance.