Recently, a major pharmaceutical manufacturer called me to help resolve a major tablet compression capacity issue. Product demand was increasing but capacity lagged behind, even after new equipment was purchased to speed up the compression machine. Operator performance was inconsistent, and increasing the campaign sizes only led to larger inventories, presenting entirely new, and unwelcome, challenges. Lothad been delayed, deadlines missed, and many heated phone calls ensued.
A clear solution for this fairly common scenario was to apply Overall Equipment Effectiveness, or OEE, one of the most effective tools that pharmaceutical manufacturers can use to manage and improve the performance of key capital assets. OEE is fairly widely used in areas such as pharmaceutical packaging, but is also being applied to processing steps. This article examines how OEE and SMED were used to manage a tablet compression machine, resulting in a 50% reduction in changeover times and a 75% decrease in changeover variability.
Unfortunately, we cannot divulge the name of the manufacturer involved, but offer the case study as an aid to companies looking to use OEE to improve unit operations and pharmaceutical manufacturing performance.
OEE, which evaluates equipment performance, availability, and product quality, systematically identifies opportunities for improvement. In this case, changeover times rather than line performance was identified as the largest cause for overall performance and variability in production. Elements of Lean and Six Sigma methodologies such as Define, Measure, Analyze, Improve and Control (DMAIC) and Single Minute Exchange of Dies (SMED) were then used to methodically eliminate waste from the changeover process without sacrificing quality or endangering compliance. In addition, standardized work, direct observation of the line, root cause analysis, and statistical process control (SPC) were used minimize variability and establish a new changeover baseline.
The Road to OEE
One of the first actions was to accurately measure the “current state”. As with any major piece of capital equipment, an equipment utilization measurement is needed. The best metric for this is OEE because it provides specific information on where to attack waste.
Relative to common measurements such as uptime, units produced, and production speed, OEE helps us understand what could have been produced and where the sources of inefficiency are located. OEE is composed of three main categories: Availability, Performance and Quality.
The Availability is the time the equipment is actually run versus the time it could have been running. A low availability rate reflects downtime from: changeovers, cleaning, shift changes lunch, breaks, etc.
The Performance is the quantity produced versus the potential quantity produced at a given run rate. A low performance rate reflects speed changes from: a slower line speed, machine downtime, lack of labor etc.
The Quality is the amount of good product versus the total product produced. A low quality rate reflects defects from: scrap and rework
In Figure 1, we are able to see how Availability, Performance and Quality are related in determining the overall effectiveness of a piece of equipment. As the bottom line output, “Good parts,” shows, the overall output of the equipment is only a fraction of its potential output. Availability, Performance, Quality can be addressed individually or in conjunction in order to improve overall productivity. (Note: TEEP, Total Effective Equipment Productivity, equates to OEE when scheduled 24/7. TEEP is not discussed here.)
In the pharmaceutical industry, many pieces of equipment have long set-up times because equipment must be torn down, cleaned up, and set back up to cGMP criteria. This time loss can represent a major loss of productivity and asset utilization (the Availability portion of OEE).
In this case, we helped identify and remove changeovers as a major contributor to Availability loss for the compression machine.
Define Stage: “Why Can’t We Make More?”
Faced with uneven output, we utilized the Six Sigma DMAIC problem-solving methodology and Lean tools to help the client identify and tackle the variable performance of the tablet compression machine. In order to best understand the usage of the equipment, historical OEE measurements were cobbled together from batch records and other available data. From this analysis it was clear that Availability losses and, more specifically, changeover times (and not throughput) was the key factor limiting the performance of the machine. Analysis of these records indicated that the shift average for changeovers was approximately 36 hours, four and a half eight-hour shifts, with a standard deviation of 16 hours.
Due to the large variation in completion time, the organization was frequently either: a) understaffed or unable to start the machine on time; or b) overstaffed and waiting to start the machine. Further, the long changeover times necessitated campaigning the different drug products produced on this line. This resulted in larger inventories.
A preliminary goal was established to reduce the overall changeover time to 18 hours (2.25 shifts), a 50% reduction.
Using the Voice of the Customer (VOC) tool, a stakeholder survey tool, the project manager interviewed key stakeholders to establish key requirements for the project. Several themes quickly emerged which helped to properly scope the project:
- Reduce cycle time
- Maintain GMP compliance
- Do not cause “atypical events” that result in investigations or quality reporting
- Do not impact product quality.
- Results must be sustainable and measurable
- Increasing head count is not an option