Design for Six Sigma and Lean Six Sigma for the Pharmaceutical and Medical Industries

By Tania Pinilla, Six Sigma Master Black Belt

Pharmaceutical companies are faced with the daunting tasks of dealing with the global economic crisis, as well as major health issues, such as the recent H1N1 swine flu virus. Companies are attempting to find ways to reduce internal costs and cycle time while maintaining a high level of service to the customer through innovative designs and efficient response to sudden increases in the demand for a product. However, balancing cost reduction and innovative design can sometimes prove to be difficult. For instance, when pharmaceutical companies merge, the intent may be to streamline costs but research and development often suffers. [1] While there is no elixir to cure these economic ails, Six Sigma and Lean methods can reduce costs while enhancing research and development in these challenging times.

“Six Sigma and Lean methods can reduce costs while enhancing research and development in these challenging times”
-Tania Pinilla

Six Sigma is a continuous improvement methodology initially developed at Motorola over twenty years ago, focusing on defect reduction using the Define-Measure-Analyze-Improve-Control (DMAIC) model, and has expanded with Design for Six Sigma and Lean Six Sigma. Design for Six Sigma centers on creating robust designs which meet the customer requirements. Lean Six Sigma focuses more on processes and how to make them more efficient. The methodologies can be used independently or in concert. Today, many companies in a diverse range of industries, both big and small, have adopted Six Sigma to improve efficiency in design, manufacturing, business processes, and intellectual property, while reducing costs. Design for Six Sigma and Lean Six Sigma can likewise be successfully applied in the Pharmaceutical and Medical Device industries to address various cost factors and impediments to profitable innovation.

This editorial will first cover the principles behind Design for Six Sigma, followed by examples of two tools commonly used – Voice of Customer and Failure Modes Effects Analysis. After which, Lean Six Sigma for process improvement is examined, along with two example applications of Lean tools – Value Stream Mapping and Just-in-Time systems.

Design for Six Sigma (DFSS)
New drugs are needed to improve health and to replace top selling drugs that will lose patent protection and face competition from, for example, generics. Finding the untapped market and need is critical to the bottom line. Once the need is found, the interactions of new drugs with existing drugs must be examined. For instance, recently a cardiologists’ group recommended patients taking heart medication should avoid certain popular heartburn pills. [2] Design for Six Sigma (DFSS) uses the Concept-Design-Optimize-Verify framework to design robust products. The underlying principle behind DFSS is understanding the unmet customer need and translating it to a technical requirement, after which statistical techniques can be used to meet and optimize the requirements. The critical first step is to clearly understand the Voice of the Customer, through techniques such as interviews or observations. A “customer” can be defined as the end user such as a patient or a doctor, or a “customer” can be a department within the organization. In DFSS, a customer is the recipient of the product under development. Through Voice of Customer activities, stories are gathered with rich descriptions of the customers’ uses that help develop a robust design.

For instance, during my time as a development engineer for an orthopedic implant manufacturer, we were planning to extend an existing hip implant system to address the growing Asian market, specifically Japan. Initially, we looked at the demographics of the target audience (elderly Asian women) and thought we simply had to add a smaller size to our already successful hip system aimed at the United States market. But upon further interviewing and observing our audience in their natural environment, performing day to day functions, we noticed that we could not simply just add another size. The range of motion of the hip required for the Asia market was something we had not encountered with the United States market. I still remember the image of an elderly Japanese woman squatting close to the ground with a large basket of rice, carefully picking pebbles out of the rice for nearly half an hour. Squatting was a common day to day activity in Asia that we had to consider and support. After engineering evaluations of the material and induced stresses, we designed an implant with an increased range of motion to specifically address this target audience. Without obtaining the true Voice of the Customer, we may have developed an implant with an inadequate range of motion that would have precluded a common daily activity – and would have ultimately failed in the marketplace.

Another aspect of DFSS is preventing defects from occurring in the first place. In the United States, the Food and Drug Administration requires risks to be evaluated and documented. Failure Modes Effects Analysis (FMEA) is an important tool in the Six Sigma tool box to help identify and prevent defects from occurring. FMEA was first developed in the 1950’s by the Aerospace industry but has been adopted by several industries, including the medical industry. FMEA uses a Risk Priority Number (RPN) to prioritize high risks. The RPN is a product of the severity of a failure mode, the likelihood of the possible root cause occurring, and the ability to detect the failure before it gets to the customer.

Once the scope of the FMEA is clearly defined, subject matter experts are gathered to brainstorm possible failure modes for each function. Using the example of the hip implant, one of the key functions of a hip implant is to support the loads on the hip. A possible failure mode of the function could be that it does not fully support the load and a severity rating is determined based on the impact of the failure mode on the customer. Root causes are generated and then a likelihood of occurrence rating is given for each root cause. A possible root cause for the example could be that the material strength of the hip implant was insufficient causing the implant to fatigue more quickly. Finally, the method of detecting and/or preventing the failure mode is evaluated. Lab testing where the implant is exposed to fatigue testing could be a control to help detect/prevent the failure mode and a rating would be given. Once RPNs are calculated, the team ranks the failure modes and ensures corrective actions are put in place to mitigate the high risk.

Figure 1: Excerpt of Failure Modes Effects Analysis (FMEA) worksheet used in Design for Six Sigma to help identify and mitigate risks using statistical tools
Attach DFSS_FMEA.jpg

Optimizing the design of the product incorporates several traditional statistical tools such as Comparative Analysis, Design of Experiments, and Reliability analysis, to name a few. At Harvard Medical School Orthopedic Biomechanics Laboratory, we evaluated several drugs purported to prevent osteoporosis and promote bone growth, which required meticulous collection of data and comprehensive analysis using techniques like comparative analysis to compare the impact of different drugs on bone density or regression analysis to understand the effect of bone density in relation to the failure load. The Design for Six Sigma framework accordingly provides tools and techniques to enhance effective product development.

Process Improvement using Lean Six Sigma
With the rising costs in the pharmaceutical industry, companies are evaluating ways to minimize waste to reduce costs and cycle time. For example, when some pharmaceutical companies merge, there may be redundant activities. Lean Six Sigma within the traditional Define-Measure-Analyze-Improve-Control (DMAIC) framework provides a way to identify redundancies and help reduce costs and cycle time in almost any process, ranging from small internal processes to larger scale manufacturing concerns, by eliminating the non-value added activities and focusing efforts on the value added activities.

Non-value added activities are defined as activities that take time and/or resources yet do not contribute to meeting a customer requirement, while value added activities are those that directly meet customer requirements. Non-value added activities can be considered “waste” and are typically grouped into three main categories – Wasting Quantity (Overproduction, Inventory, Transporting), Wasting People’s Capability (Waiting, Motion, Processing), or Wasting Quality. One of the tools to help lay a blueprint of the flow of activities is Value Stream Mapping.

Figure 2: Identifying Non-Value Added and Value Added Activities is key to a Lean process
Attach LEAN_Value.jpg

With Value Stream Mapping (VSM), experts who live and breathe the process are gathered and the process is carefully observed, to develop a current state map, showing the process as it currently stands, with both value added and non-value added activities. Details such as cycle time, number of operators, shifts etc are also captured, along with the inputs and outputs of each process step. Value added and non-value added times are totaled. Once the map is finalized, the team discusses the activities and develops solutions to eliminate the waste. A future state map is outlined, showing the reduction in waste. Traditional six sigma tools such as control charts can then be applied to ensure the new process is consistent over time.

Another current pharmaceutical issue that could lend itself to Lean techniques is the rapid development and production of vaccines for the H1N1 swine flu virus. Pharmaceutical companies are expected to develop a safe vaccine as quickly as possible and, if needed, mass produce it immediately. Once cases are confirmed, companies around the world await for strains of the virus to begin making vaccines. The traditional egg-based vaccine process involves injecting the virus into fertilized eggs, allowing the virus to multiply within the embryonic fluid. Once the virus can be grown and prepared to become a vaccine, researchers repeat the process on a larger scale.

If this process was evaluated using Lean techniques, a value stream map would outline the flow of vaccine development. Some pharmaceutical companies have already recognized one of the long lead items and are taking steps to further develop a quicker method of creating vaccines, such as cell-based production. Other areas in the process, including the manufacturing side, can be examined to reduce cycle time.

On the manufacturing side of the vaccine production process, companies need to be prepared to balance mass production with excess inventory. Just in Time (JIT) manufacturing within Lean Six Sigma prevents overproduction and uncontrolled inventory, and improves flexibility to schedule and react to changing customer requirements. In simple terms, it is a method of pulling inventory rather than pushing. A common analogy of pull versus push is trying to move a chain laying on a table from left to right. If you push the left most link, the links bunch together and the chain barely moves. However, if you pull the right most link, the chain moves easily across the table.

Drug manufacturing lends itself well to the pull philosophy, as too many drugs waiting in inventory risk expiration. The pull process also provides a more consistent Work In Process, which helps achieve shorter and more predictable manufacturing cycle time. A JIT process centers around the customer – produce what the customer wants, when the customer wants, in the numbers the customer wants. Internally, we want to meet those customer needs by using minimal amount of inventory, capacity, space, and labor. Once an optimized process is determined, the cycle time for a JIT process can then be simulated using a technique called Monte Carlo Simulation, which accounts for variations in each of the steps to obtain a more realistic model. The Lean techniques shown focus on driving down cycle time and improving the process flow.

Summary
The current environment provides a particularly rich opportunity for companies to evaluate their internal processes and employ new techniques to sustain a profitable business. Simply addressing costs may stifle product development. A combination of Design for Six Sigma and Lean techniques can help achieve a successful balance. Companies using Six Sigma typically have strong upper management support driving the initiative, and Six Sigma trained personnel (ranging from the basic skills of a Six Sigma Green Belt to the more advanced Black Belt or Master Black Belt) within the organization to help facilitate methodology and tool use. The examples shared simply touch the surface of the many applicable tools within the Six Sigma frameworks to address various product or process challenges.

Tania Pinilla has been in the engineering industry for 17 years and is currently a certified Six Sigma Master Black Belt at Motorola, teaching and driving DFSS. Her earlier experience was in product development, designing cellular products. Prior to Motorola, she worked as a Development Engineer at Zimmer Orthopedics, and a Research Engineer at Harvard Medical Orthopedic Biomechanics Laboratory. She holds a Mechanical Engineering degree from the Massachusetts Institute of Technology.

References:
[1] http://www.businessweek.com/technology/content/mar2009/tc2009039_020072.htm
[2] Wall Street Journal – May 7, 2009 Vol. CCLIII NO. 106, D1