Application of Overall Equipment Effectiveness to Biopharmaceutical Manufacturing - Overall equipment effectiveness is an ideal measure for capital equipment-intensive businesses such as biopharmaceut


Application of Overall Equipment Effectiveness to Biopharmaceutical Manufacturing
Overall equipment effectiveness is an ideal measure for capital equipment-intensive businesses such as biopharmaceutical manufacturing.

BioPharm International
Volume 22, Issue 5


Total Productive Maintenance

Total productive maintenance (TPM) aims to maximize equipment productivity during its service lifecycle and extend its length of useful service. OEE is a basic building block for TPM because it quantifies both loss types and their durations to appropriately focus on improvement activities.24 TPM analyzes reasons for equipment waste (such as repeated similar repairs and inadequate training) to improve OEE, thus reducing equipment duplication and freeing-up valuable processing space. Its goals are zero breakdowns, speed losses, defects, and accidents.17 It focuses on autonomous maintenance by operators through small group activities to develop ownership, and improving relationships among people, processes, and equipment.19,21,24 Equipment reliability, not only its downtime (availability) but also underuse relative to installed capabilities (performance), minimizes compensating purchases of duplicate units of expensive or large footprint equipment.24 Without OEE, organizations unknowingly invest capital, and thus OEE data can support or challenge capital proposals.24

Related to total productive maintenance, total preventative maintenance focuses on preventing breakdowns rather than fixing broken equipment, also including operators in maintenance and monitoring activities.25 Strategies exist to reduce losses caused by inadequate spare part stocks, attempting to achieve zero losses with the lowest spare part inventory possibly by eliminating waiting time for critical spares.26

Set Up Reduction

Single minute exchange of dies (SMED) aims to reduce equipment downtime consumed by changeovers and set ups associated with switching products.27 It is particularly applicable to biomanufacturing facilities that have multiproduct suites. Downtime is measured as the time from the last good product of type A to first good product of type B.1 Set up reduction helps meet increased customer multiproduct demand because some changeover times can be longer than product cycle times, dramatically reducing suite availability.1 Changeover activities are classified as internal or external based on their ability to be executed during processing of the previous product.17 The next step is to reduce, eliminate, or convert as many internal activities to external, and then progressively shorten remaining internal activity times.1,17

Theory of Constraints

The theory of constraints is a five-step cycle to identify constraints that restrain production systems from achieving high overall operational excellence.28 The five steps include:

  • Step 1—Preparation: a system flowchart is developed. Productivity parameters are defined along with metrics to guide data collection.
  • Step 2—Metrics: metrics are calculated at the equipment, subsystem, and system levels.
  • Step 3—Root cause analysis: bottleneck productivity is evaluated (using Aeff, Peff, and Qeff) and losses identified at upstream and downstream of the bottleneck.
  • Step 4—Simulation: the limiting constraint is identified, then simulation is used to assess various scenarios for its removal.
  • Step 5—Repeat: the entire cycle is repeated to identify and eliminate new constraints.

This strategy can be applied to develop alternatives to alleviate the current purification bottleneck in biomanufacturing because of the rise of bioreactor product titers.29

Generic Problem-Solving Process

A generic problem-solving process can be used in biomanufacturing to efficiently remove OEE limitations.30 The simple steps for this process are: (1) recognition that a problem exists that should be solved; (2) allocation of appropriate priority to develop the solution (i.e., identify possible causes and alternative solutions, and then selecting a solution); and (3) solution monitoring to determine its effectiveness.31

Armed with flow charts, assembled cross-functional teams review the step and its support functions to identify failures, calculate failure values (i.e., failure type x frequency x loss per failure x values per loss), prioritize losses with the greatest improvement opportunity, and then select appropriate solutions to minimize future losses.32

Key to OEE Success

Key factors to using OEE to drive biomanufacturing improvement initiatives are consistent data capture and regular OEE calculations.1 Although OEE jointly measures the efficiency and effectiveness of operations and maintenance, it is not always sufficiently detailed to indicate precisely how and where to focus improvement resources.31,33 Used alone, OEE is a high-level operational measure that might mask counteracting variations in availability, performance, and quality in some biomanufacturing applications.31 Consequently, estimation of OEE's component terms along with the calculated OEE value, can elucidate improvement opportunities, particularly in biopharmaceutical manufacturing.


1. Burns A. Choosing the right tool from the toolbox. IEE Seminar Kaizen from Understanding to Action. 2000;IEE 6/1–10.

2. Muthiah KMN, Huang SH. Overall throughput effectiveness (OTE) metric for factory-level performance monitoring and bottleneck detection. Int J Prod Res. 2007;45(20):4753–69.

3. Pomorski T. Managing overall equipment effectiveness (OEE) to optimize factory performance. 1997 IEEE Inter Sym on Semicond Manuf Conf Proc. Piscataway, NJ: IEEE; 1997. pp. A33–A36.

4. Scott D. Overall factory effectiveness, the corollary to Moore's law. Machine Design. 1999. 71:22,170.

5. Juric Z, Sanchez AI, Goti A. Money-based overall equipment effectiveness. Hydrocarbon Processing. 2006;85(5):43–5.

6. Oechsner R, Pfeffer M, Pfitzner L, Binder H, Müller E, Vonderstrass T. From overall equipment efficiency (OEE) to overall Fab effectiveness (OFE). Materials Science in Semiconductor Processing. 2003;5:333–9.

7. Tal O. Overall resources effectiveness, the key for cycle time reduction & capacity improvements. GaAs Mantech Conference; 2001; Las Vegas, NV. pp. 255–8.

8. Scott D. Can CIM improve overall factory effectiveness? Proceedings of the Pan Pacific Microelectronics Symposium; 1999. pp. 411–24.

9. Scott D, Pisa R. Can overall factory effectiveness prolong Moore's Law? Solid State Technol. 1998;41:3,75–82.

10. Fogelholm J. Assessment of main stages in productivity steering in mills. Paperi Ja Puu-paper & Timber. 2006;88(6):342–7.

11. Pauwels J. Closing the manufacturing productivity gap through service solutions. J ABB Automation Technol. 2004;34–5.

12. Allcock A. Understanding OEE. Machinery. 2004;162(4102):16–7.

13. Gregory A. Number cruncher. Works Management. 2006;58(7):18

14. Johnson M. Manufacturing improvement in the paper industry. Paper Technol. 2005;46(7):33–6.

15. Dismukes JP, Vonderembse MA, Chandrasekaran S, Hudspeth L, Caldwell WP. Opportunities for radical innovation in flat glass production operations. Ceramic Engineering and Science Proceedings. 2000;21:1,9–29.

16. Sarkar BN. Capability enhancement of a metal casting process in a small steel foundry through Six Sigma; a case study. Int J Six Sigma and Competitive Advantage. 2007;3(1):56–71.

17. Hide L. 2003. Using overall productivity efficiency (OPE) as a catch-all metric for package printers. Improving Package Printing. Pira Int. Surrey, UK; 2003. pp. 1–9.

18. Jacobs JH, Etman LFP, van Campen EJJ, Rooda JE. Characterization of operational time variability using effective process times. IEEE Transactions on semiconductor manufacturing. 2003;16(3):511–20.

19. Pendrous R. Effective choices. Food Manuf. 2002;77(1):30–2.

20. De Ron AJ, Rooda JE. Equipment effectiveness: OEE revisited. IEEE Transactions on Semiconductor Manuf. 2005;18(1):190–6.

21. Gouvea da Costa SE, Pinheiro de Lima E. Uses and misuses of the overall equipment effectiveness for production management. IEEE International Engineering Management Conf, Cambridge, UK; 2002. pp. 816–20.

22. Bharadwaj S. Pharmaceutical manufacturers set sights on best-in-class operations performance. Pharmaceutical Processing. 2008;24(1):14–20.

23. Brochu DL. Using metrics to manage improve performance. Plant Eng. 2007;61:6,37–41.

24. Godfrey P. Overall equipment effectiveness. Manuf Eng. 2002;81(3):109–12.

25. Abdulmalek FA, Rajgopal J. Analyzing the benefits of lean manufacturing and value stream mapping via simulation: A process sector case study. Int J Prod Econ. 2007;107:223–36.

26. Owens S, Miller S, Deans D. Availability optimization using spares modeling and the six sigma process. Annual reliability and maintainability symposium, Jan 2006. Newport Beach, CA.

27. Rivera L, Chen F. Measuring the impact of Lean tools on the cost-time investment of a product using cost-time profiles. Robotics and Computer Integrated Manuf. 2007;23:684–9.

28. Huang SH, Dismukes JP, Shi J, Su Q, Wang G, Razzak MA, Robinson DE. Manufacturing system modeling for productivity improvement. J Manuf Systems. 2002;21(4):249–59.

29. Thiel KA. Biomanufacturing from bust to bubble? Nature Biotechnol. 2004;22:1365–72.

30. Gottschalk U. New and unknown challenges facing biomanufacturing: An editorial. Biopharm Int. 2005;18(3):24–8.

30. Francis R. Providing productive capacity. 59th Appita Annual Conference & Exhibition. Vol. 1, Paper 1B33, 2005;67–74.

31. Moore R. Improvement projects and tools: Where to start and what to use. Plant Engineering. 2003;57(3):30–2.

32. Jonsson P, Lesshammar M. Measuring manufacturing performance: Dimensions and OEE. In: D.F. Kocaoglu, T.R. Anderson, D. Milosevic, K. Niwa, M.J. Gregory editors. Innovation in technology management—The key to global leadership. PICMET. Portland, OR; 1997. pp. 799.

33. Clark R. Concise OEE made E-A-S-Y. Tooling and Prod. 2005;71(12):13.

34. Hutchins D. Introduction TPM. Manufacturing Engineer. 1998;77(1):34–6.

35. Kotze D. Consistency, accuracy lead to maximum OEE benefits, TPM Newsletter, AITPM, Productivity, Inc. Norwalk. 1993;4(2):1–4

36. Herron C, Braiden PM. Defining the foundation of lean manufacturing in the context of its origins (Japan). Agile Manufacturing (ICAM), Institution of Engineering and Technology Manufacturing Enterprise, Page Bros (Norwich) Ltd, Great Britain; 2007. pp. 148–57.

37. Dance DL, Jimenez DW, Levine AL. Understanding equipment cost-of-ownership. Semiconductor Int. 1998;21(8):117–122.

Beth H. Junker is senior director of fermentation and development operations at Merck Research Laboratories Rahway, NJ, 732.594.7010,

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