Pharmaceutical manufacturers continually strive to improve the quality of their products along with improving their production operations. Over the years, many manufacturers empowered their workforce to follow the management techniques of Six Sigma — the statistical-based, data-driven method to reduce costs and increase profits, and Kaizen — the gradual and methodical process to boost productivity by improving the work environment. These initiatives can bring improvements to an operation as long as the manufacturer has a structured means of measuring the results by hour, shift, day, week and so on. One such key performance indicator, or KPI, is Overall Equipment Effectiveness (OEE).
OEE is a measure of how effectively a manufacturing operation is being utilized. The term OEE has been around for over 50 years, created by Seiichi Nakajima, a Japanese citizen and pioneer of the Total Productive Maintenance system. OEE is most effectively applied in production where “units” are produced or created, such as capsules, vials, bottles, syringes, intravenous (IV) bags and packaging (blister packs, cartons, cases, kiting and pallets). A production operation’s OEE value is measured in percentages and is based on three factors:
Availability [A], Performance [P] and Quality [Q].
OEE = A x P x Q
Availability = Run Time/Planned Production Time; Run time is negatively affected by occurrences of downtime.
Performance = (Ideal Cycle Time x Total Count)/Run Time; Also referred to as “throughput,” a measure of how close production is running to the maximum possible speed.
Quality = Good Count/Total Count; Good count is defined as units that meet quality standards on a first pass basis; aka, no rework or total rejects.
A well-run pharmaceutical manufacturing facility concentrates on maximizing both productivity (the measurement of output over time) and efficiency. OEE addresses both in the same calculation. The many components of OEE can become very useful KPIs for several of the operational groups of a manufacturing facility including production, engineering, maintenance and management.
Some pharmaceutical manufacturers have been utilizing OEE for many years; others not yet. This split between embracing/not embracing OEE in pharma is no different than other manufacturing industries. Costs to implement OEE and the corresponding ROI become key factors in the decision of whether or not to implement OEE.
Implementing OEE in a manufacturing facility typically requires a capital investment. The magnitude of the investment is heavily dependent on the number of components of the production line, their age and the type of machine controllers used in the manufacturing operation. OEE starts at the work cell level, which can include a process unit such as a batch tank or fermenter, but more commonly includes filling and packaging equipment such as fillers, cappers, checkweighers, labelers, cartoners, casepackers or bundlers. Key to the success of implementing OEE in manufacturing is the crucial step of verifying the data being extracted from each work cell, including root cause for downtime and stoppages.
A properly designed, configured and verified OEE system can deliver timely and meaningful information geared towards improvements in pharmaceutical manufacturing.
OEE Q&A WITH INDUSTRY LEADERS
How can OEE help pharma companies?
Tim Gellner, Senior Consultant, MAVERICK Technologies: Implementing an OEE program is an essential part of the overall continuous improvement process. If done properly, OEE provides the framework of standardized methods for the acquisition, analysis and reporting of a broad range of production data, which is key to understanding the true performance (both good and bad) of the manufacturing equipment.
The OEE number that results from the calculation model is a good indicator of performance; however, the real power of the OEE calculation model is the constituent data that goes into it. Through the analysis of the components of availability, performance and quality, the root causes of production losses can be quickly identified and acted on. With the near universal implementation of automated production equipment, and using automated analysis and reporting tools, the root causes of losses can be identified in near real-time.
Steve Malyszko, President, CEO, Malisko Engineering: Implementing an OEE system can help pharma manufacturers improve operational efficiency and increase productivity when they are experiencing any one, or all, of the following situations:
When the manufacturer is having difficulty filling orders on time due to limitations, restrictions, or problems on the manufacturing line and doesn’t have a way to capture and analyze downtime and quality data.
When the manufacturer has a “gut feel” that they can improve production efficiency but they don’t have a system to capture the root cause(s) of downtime and poor quality.
A real-world example we saw was a pharma manufacturing client who had difficulty meeting their scheduled speeds on a multi-dose line. Very shortly after we activated the OEE system, the manufacturer quickly found the major pinch-point was the filler. Additionally, the client found that the operators were pressing the emergency stop button anytime the operators wanted to or needed to pause filling. E-Stop completely shuts down the filler and removes all electrical power; pause merely pauses the filling operation, keeping the system powered. Rebooting or restarting the filler after E-Stop took several minutes, thus causing excessive and unnecessary downtime. The OEE system captured this incorrect procedure and caused production to re-train the operators to press pause instead of E-Stop, thus significantly increasing filler run time.
Additionally, contract manufacturers can benefit from implementing an OEE system when they’re contractually required to meet specific production rates to meet their clients’ orders. OEE can help quickly point out their work cell(s) not meeting acceptable OEE thresholds.
We had a contract manufacturing client have us deploy an OEE system as part of a new line they were installing in order to fulfill their contractual unit production obligations. The CMO knew the system would be crucial for them to monitor and quickly react to correct any work cell operation not meeting its OEE threshold.
Do you think pharma manufacturers are lagging behind other industries in OEE? If so, why?
Steve Malyszko, Malisko Engineering: Some pharmaceutical manufacturers have been utilizing OEE for many years; others not yet. This trend of embracing or not embracing OEE in pharma is no different than other manufacturing industries such as food and beverage. Costs to implement OEE and the corresponding ROI become key factors in the decision of whether or not to implement OEE.
Rodney Rusk, Industry 4.0 Business Leader, Bosch Rexroth: Although OEE data is critical to the continuous improvement process (CIP), it is even more critical in those segments of industry that are focused on medical devices and pharmaceuticals due to the dynamic regulatory requirements, liability mitigation measures, production cost, containment demands and overall consumer safety protocols.
In most cases, the use of OEE data in the pharma industry is farther advanced than other industries. Many of the modern drivers for this use of OEE data, along with lean principles and CIP, arose after the Tylenol product tampering scandals and resulting deaths of 1982. Examples of these foundational changes were then indirectly launched by the U.S. Federal Anti-Tampering Act of 1983.
Today, thanks to the continued advancement in hard drive processing power — as predicted under Moore’s Law in 1970 that says the speed of technology doubles every two years — the pharma industry continues to advance in both the use of OEE data, as well as the implementation of connected industry solutions to provide even better real-time monitoring and faster reaction times to changes in production or problem solving. More than 60 percent of the industry has moved or is in the process of moving to remote data access systems that bring the data from the traditional localized production floor to the front offices and even outside of the production facility.
What are some keys to implementing an OEE program?
Tim Gellner, MAVERICK Technologies: An OEE program implementation should promote continuous improvement through alignment, standardization and cultural change, by addressing the following key points:
Alignment: The key stakeholders in the organization understand and agree to the vision for the OEE program implementation.
Definitions: The OEE metric and its component factors must be well-defined, provide apples-to-apples comparisons and should not impose arbitrary or unrealistic targets.
Downtime: Gathering and analyzing standard downtime reasons is critical in root cause analysis and in providing the basis of accurate comparisons.
Analysis: It’s imperative that the methods employed for the OEE data analysis provide the basis for affecting improvement. It’s also important that the data be presented in a manner suitable to preserve its context while allowing for readily distinguishing between normal and exceptional process variations. Standardized analysis methods promote moving from production metrics driven by targets, to those that promote and deliver continuous improvement through analysis. One example of this is using Process Behavior Charts, which graphically show process variations over time and help distinguish between normal and exceptional process variations.
Rodney Rusk, Bosch Rexroth: With the advent of the 4th Industrial Revolution (or Evolution), the use of OEE data and the technology to analyze, optimize and share that data is finally here. In addition, the processing power available now makes real machine learning possible. Most industries that are embracing a digital transformation are seeking this ultimate goal: self-learning production machines that provide real-time, data-driven responses to production issues and that can be shared beyond the work cell on a plant floor, geographic region or global footprint. In order to get there, these companies need to not only evaluate the new technologies that are available, but also need to do several other activities:
- Re-examine both our current OEE data that has been utilized to-date as well as lean processes.
- Re-engage the human elements within operations.
- Proactively plan how to handle OEE data collaboration solutions.
- Select partner companies to work with you on your current and future roadmap.
What should the next steps be to improve OEE for the industry?
Rodney Rusk, Bosch Rexroth: The future of OEE data in the medical and pharmaceutical production arenas will change dramatically as technology development and adoption speed up. Although there are myriad potential new technologies that could be applied to expand OEE data points and optimize OEE data through verification and monitoring, three trends stand out as those to watch:
Augmented reality technology (such as smart glasses, wearables or 3D projection/overlay devices) that can be utilized for manual or semi-manual production systems to insure process flow and quality validation. This technology could provide very valuable data points for process development, human error avoidance and OEE data analysis.
Data security, ransomware and firewall security from data tampering or intrusion by outside entities that seek to do harm or hijack proprietary information. As technology continues to advance, so will outside forces that have agendas that are not aligned .
Governmental regulation from agencies or other bodies that have purview over liability, safety, worker rights and data protection policies will need to keep pace with the technology. If recent history shows us anything, most governmental bodies and agencies are not keeping up with technology and remain slow to move.
Editor's Note: Introduction written by Stephen Malyszko, P.E., President & CEO, Malisko Engineering Inc.
Malisko Engineering is a certified member, Maverick Technologies is a member, and Bosch-Rexroth is a partner of the Control System Integrators Association (CSIA). For more information, visit the Industrial Automation Exchange
[javascriptSnippet]
