Lean Six Sigma

Waste in Laboratories

Tom Reynolds — Thu, 17 Jan 2019 21:46:01 +0000

Published by Tom Reynolds in Lean Laboratory on January 17, 2019

Laboratories are not the same as manufacturing environments so do the standard Lean ‘Wastes’ even apply in Labs?

The term ‘Lean’ was first coined in 1990 to describe the manufacturing approach being used in Toyota factories in Japan. The “Toyota Production System” (or TPS) as it was called locally had been developed mostly by Taichii Ohno a mechanical engineer who rose through the ranks to become Executive Vice-president.

TPS shifted the focus of improvement initiatives from individual machines and their utilisation, to the flow of the product through the total process. Toyota understood that they could create ‘flow’ and reduce waste by lining their machines up in process sequence, developing quick set-ups (so that each machine could make small volumes of many part numbers) and by having each process step notify the previous step of its current needs for materials (i.e. pull). This in turn made it possible to achieve low cost, high quality, and rapid throughput times with high product variety.

“Add Nothing But Value” (Eliminate Waste)

In developing the Toyota Production System, Ohno identified 3 primary wastes - Mura, Muri and Muda in Japanese and seven (now famous) sub categories of Muda. Elimination of these wastes is the basis of most lean projects but are they relevant in the Lab environment?

Mura

Mura (unevenness) is the waste associated with volitile workloads. If anything, Mura is even more significant in Labs than in traditional manufacturing. In most labs there is short term volatility in the incoming workload with significant peaks and troughs. More often than not, this volatility is imported directly into the testing process which causes low productivity (during troughs) and poor lead time performance (during peaks). Levelling a volatile workload is perhaps the single most valuable thing that can be done when leaning a lab.

The simplest levelling strategy is to create the ability to process samples at the 'levelled demand rate' quickly (via flow). This reduces the 'throughput' time and incoming samples can then be held in a 'levelling queue' at the start of the process and released into the lab as part of a level daily volume and mix.

Muri

Muri (overburden) is the over loading of people or equipment. In Ohno’s world this included physical strain. In Labs a form of Muri is often directly caused by Mura when analysts are overloaded in an attempt to deal with peaks in the workload. ‘Muri’ can be avoided via levelling and defined analyst roles based on a repeating sequence of testing that meets levelled demand. It can be done!

Muda

Muda (waste) – Muda is any activity that doesn't add value (as defined by the customer). Ohno defined 7 forms of Muda and while most of these can be found in Labs, individual wastes may not be as significant in a Lab context as they are in manufacturing.

A cautionary note: The significance of Mura and Muri is often misunderstood and underestimated and many Lean Lab projects focus only on the Muda. There is a simple reason for this, waste is easy see and understand and tools like Value Stream Mapping help identify lots of new wastes to work on. Whereas tackling Mura and Muri is much more challenging particularly in Labs.

Eliminating waste from a levelled flowed lab process, instead of at isolated points creates processes that need less human effort, less space, and less time to test samples at less cost and with fewer errors and test failures, than traditional labs. Lean labs are also able to respond to changing customer priorities with fast throughput times.

Our consultants can provide further information on the above and discuss any aspect of Real Lean Transformation, simply set-up a call today.

Improving Lab Performance with Six Sigma

Andrew Harte — Tue, 04 Sep 2018 20:19:56 +0000

Published by Andrew Harte in Lean Laboratory on September 4, 2018

Do you want to reduce lead times while improving productivity in your QC testing laboratory? Read the following case study to find out how.

This case study shows how a lean six sigma project at a leading global pharmaceutical company managed to reduce lead times while improving productivity in their QC testing laboratory using the DMAIC approach.

Lean and six sigma have been popular methodologies in manufacturing for years and are now beginning to migrate outside of their traditional manufacturing habitat. However there are challenges in implementing these methodologies in other areas. Laboratories are a taxing environment in which to implement lean and six sigma but creative adaptation of the techniques can deliver significant improvements in cost or speed.

Define Lean Lab Goals

Defining the goals of any lean laboratory project seems like a simple task, but it is critical to whether the project will be viewed as worthwhile by the wider company and top management. The goals of the project should be chosen to mirror those of the business. In this case the goals of the site were to reduce “End to End” cycle time of their products while keeping the cost per unit as low as possible. The goals of the lab project were picked to mirror these, i.e. to reduce the cycle time for testing and release of product and to do so as productively as possible.

Tools such as Pareto plots and value stream maps are useful in deciding where the focus of a lean laboratory project is to be. A Pareto analysis of the incoming laboratory workload revealed that the majority of the workload (85-95%) is driven by 2-3 products. In situations like this, the most benefit can be obtained by focusing on these products.

Product A and C were from the same product family, received the same tests and could be tested together at the same time. While Product B accounted for 19% of the sample volume it did not account for 19% of the labs workload as it only required two very simple tests, while A and C received nine different tests. The project team decided to focus exclusively on A and C as it accounted for 80-90% of the labs workload and was the main priority of the site.

Fig 1: Volume by Product Type
The “As is” Process Map revealed a significant portion of the cycle time is due to the approval and release activities carried out after the batches were fully tested. As a result it was decided that approval activities would also be within the scope of the project.

Measure Lean Lab Performance

The Measure phase of the project was to establish valid reliable metrics to monitor progress towards the chosen goals. The lab already had in place metrics on cycle time. A look at the breakdown of cycle times for Product A showed a spread of times centred around 11-15 days which corresponded to the labs target cycle time of 15 days. 66% of samples met the 15 day target time while 33% of samples were late. The average cycle time was 14.8 days.

Fig 2: Product A Cycle Times (Jan - Apr)
Looking at resourcing in the lab, it was immediately striking that the vast bulk of the resources were occupied by one test; test x. The results of this test were required by a separate department to proceed with their process. As a result the laboratory heavily resourced this test with the aim of trying to test every sample every day. This was inefficient as it resulted in variable numbers of samples tested each day. For example, on one day, five analysts might test 12 samples and the following day they may only test 4, a 67% drop in productivity from one day to the next. A strategy was required that would be consistently productive without adversely affecting cycle times. To do this it would be necessary to control the number of samples tested each day.

Analyze Data

The Analyze phase of the project looked at all the available data to determine the best way to move towards the desired goals of the project. It was found that:

Daily the lab received between 1 and 17 samples resulting in an average of 7 per day.
Weekly the lab received between 25 to 45 samples resulting in an average of 36 per week.
The weekly incoming workload was much less volatile than the daily pattern (coefficient of variance 0.2 versus 0.6).

So, although it was not possible to predict how many samples would arrive on a given day, it was possible to say with reasonable certainty that over the week the lab would receive approximately 36 samples. It was clear that it would be possible to have some level of control over the number of samples tested if a weekly testing pattern was developed due to the smaller weekly variation. Next, the weekly average (or takt rate) for each test was determined. The number of samples for each test would be different as Product A received some tests that product C did not and vice versa.

Having analyzed and reviewed all of the data a clear strategy was decided upon. The lab would run:

A fixed, weekly repeating pattern of tests (a Rhythm Wheel).
Testing at the weekly average every week i.e. testing at the weekly takt rate.
Every test would be run every week.
Samples would be tested in FIFO (first in first out) order.

In reality a figure slightly above the average had to be picked in order to cope with the expected weekly volatility, deliver acceptable lead times and account for failures/repeat testing. It was obvious that to follow this strategy some test would have to be run more often. So as not to negatively impact productivity, it was decided to reduce capacity for some tests (e.g. test x) in order to take resources from those tests and use them to increase capacity for other tests so that the overall cycle time for each of the tests would be closer to each other (a batch is only as fast as its slowest test).

Improve Lab Productivity

To improve productivity and ensure consistent results the team developed standard work for each of our testing roles. The team set about identifying:

The optimum number of samples for one analyst to test in one shift.
The best order in which to perform test activities.
Any improvements that could be made to the process.
Long periods of inactive time that could be used to run other short tests.
How many times to run the test each week.

Because the system controls what tests occur each day it removes much of the unpredictability and volatility that individual analysts experience in day to day testing. This provides consistent results thus ensuring both productivity and consistently low lead times.

There was concern over what effect the rhythm wheel would have on lead times for test x, so it was agreed that before any changes were made the team would model the outcome for this test. Using actual data from the previous 6 months, the model showed that, 49% of samples would have been tested the day they arrived, 31% the next day and the remainder after two days. This was deemed acceptable by all affected process owners.

Advantages of the rhythm wheel:

It was vastly more productive than the old system, requiring only 40 FTE shifts versus 54, (a 26% improvement).
It removed the uncertainty around the equipment capacity and avoided equipment conflicts.
It removed a lot of the stress and scrambling from the daily testing routine for the analysts.
Every test is run every week to ensure consistent and short lead times.

In the define phase the “As is” Process Map revealed a significant portion of the cycle time was due to the approval and release activities. To address this, the review and approval process was reengineered to remove this delay by operating to the laboratories testing takt rate and reviewing every batch every day.

Once all the changes were implemented average cycle times tumbled from 15 to 8 days. The overall laboratory headcount was reduced from 20 testing analysts to 15, a 25% productivity improvement.

Control Phase

The Control phase of the project was initiated to ensure that the lead time and productivity gains established from the project would not be lost or eroded over time. To ensure that analysts knew exactly what was expected of them and to ensure that the productive roles developed from the test templates were not diluted, the team designed set roles which clearly showed:

The activities required for the test role.
The best order in which to complete them.
Clear break targets.

The roles were very successful at sustaining the productive roles within the laboratory.

The KPI’s (key performance indicators) were printed and posted weekly to show exactly how the labs cycle time performance was. There was a definite moral boost to the lab to see the lab performance consistently ahead of their targets. Before the six sigma lean lab project 66% of samples were tested inside the 15 day target time. After the project was completed the target was changed to 10 days, and all samples were consistently tested within the target time, with an average lead time of 8 days. There was an annualised 3.9 fold return on investment for the project (ROI).

Our consultants can provide further information on the above and discuss any aspect of Real Lean Transformation, simply set-up a call today.

Lean Organisation for Lean Programmes

Pat Sheehan — Wed, 11 Apr 2018 16:26:47 +0000

Published by Pat Sheehan in Lean Programs on April 11, 2018

Here’s the Scenario: You’re a site leader three months into your Lean Programme and on the face of it things are going well but you’ve got doubts that the organisation structure is supporting your lean journey in the way you’d want. These are some of the contradictions that you see.

For the first time you’re measuring OEE, you can see your Pareto of losses and the production team are busy applying SMED to reduce changeover times… BUT your engineers still see themselves as a service to production, they measure KPI’s that are not aligned to OEE improvement (for example the number and age of open engineering work orders), technical expertise is spread too thin, they spend too much time on what should be autonomous maintenance tasks and they don’t attend the daily start of shift meeting to be appraised of the issues of the day.

Neither is your quality organisation best supporting your quest for continuous improvement; they spend 80% of their time auditing, reporting and issuing action lists and only 20% of their time actively solving problems.

The impact of demand volatility has been explained to you and you’ve helped design a fixed repeating levelled schedule that delivers flow and repeatability but your planners want to retain central control for planning and scheduling and insist on making planning more complicated than it really is.

Your newly designed Work Instructions (WI’s) are concise and user friendly but you rely on your already stretched production supervisor to train out the operators when she can. You’d like to have someone in a Team leader role spending 80% of his time managing this important standardisation activity.

Finally as a senior team you’ve got all the lean training and practical problem solving training you could wish for but you’re not actively solving problems with your team and you certainly don’t see yourself as being confident when it comes to teaching the Lean System.

It’s time to get serious about designing an Ideal Future Organisation Structure that really supports your Lean endeavours and integrates functions and activities in a way that maximises your continuous improvement efforts.

Here’s how you might go about this task

Establish the scale of the change you require

Think about dividing up the site into mini business units / value streams based on product family or technology to make them more manageable.
Decide whether you should examine all functions on the site or initially focus on integrating those that are closely aligned to day to day production activities (Engineering, Quality, Planning, HR, etc)?

Define and document the current organogram

This will bring a clarity to the task ahead (and probably prompt a lot of questions, like why on earth does this role exist, etc).

Identify possible opportunities for change - ask yourself…

How do I get more / better support in the areas I need it?
How do I design Roles that have more of a Lean Focus?
Suppose I had fewer planners, functional supervisors, QC auditors, etc, etc…what would that look like?
How can I avoid duplication of effort?
How can I simplify how issues are uncovered and resolved?
How can I improve focus and give more autonomy?
How will the senior team on site organise itself be best equipped to lead and teach the Lean system?
How do I create a better environment to work in for everyone?

Examine each opportunity in detail

Quantify tasks.
Assess the pro’s and con’s of the change and then Decide!
Compile Ideal Future Organisation (IFO) map.

Agree an Implementation Strategy

Should I go “Big Bang” or opportunistically over a longer period?
Prepare a detailed implementation plan.
Communicate, Communicate, Communicate!!
Prepare a roadmap with milestones for completion.

Tips to follow

Don’t try to reinvent the wheel – what you should end up with should resemble the Toyota Production System Model.
Designing an IFO is a task for the senior team not a lean project team.

Our consultants can provide further information on the above and discuss any aspect of Real Lean Transformation, simply set-up a call today.

Lean Thinking for Laboratories

Tom Reynolds — Thu, 05 May 2011 14:57:50 +0000

Published by Tom Reynolds in Lean Laboratory, Lean R&D on May 5, 2011

While it might sound like some sort of fad diet, “lean” in the context of business improvement refers to a specific methodology that originated in the Japanese motor industry toward the end of the 1980s. Over the decades, this lean philosophy has been successfully adopted by many companies across a broad spectrum of industries and, more recently, lean thinking has filtered into laboratories. The focus of a lean laboratory is to test samples in the most efficient way possible in terms of cost, or speed, or both. Although most of the key principles of lean apply in labs, the specific challenges facing laboratories require significant adaptation of standard lean tools.

Laboratories are typically faced with more volatility and variation in the type and volume of work they are required to perform than are manufacturing operations. The life science industry is faced with the additional layer of GMP and GLP complexity. In this context, attention to efficiency and productivity is often secondary. However, there is in fact no inherent conflict between efficiency and compliance. Lean processes in a laboratory achieve regulatory compliance in the most efficient and productive manner possible. A lean lab welcomes auditors and delights in the opportunity to showcase its process improvements along with its capacity to satisfy not just regulators, but customers (internal and external) too.

The factors affecting laboratory performance

Performance in today’s laboratories tends to be negatively affected by a number of issues. These include:

Volatile incoming workload

Most labs experience a volatile incoming workload, with significant peaks and troughs. This results in low productivity during troughs and/or poor lead-time performance during peaks. Understanding laboratory capacity and resource requirements and leveling workloads in a meaningful way is the crux of “leaning” a laboratory. The surest way to fail is to put more work into the lab than it can handle!

Too much WIP (Work in Progress)

Samples do not “flow.” While laboratory analysts may progress speedily through testing, haphazard scheduling resulting from cross-training deficiencies and instrument conflicts means that, at a given time, many samples are partially tested but few are fully completed. Lean in the laboratory means performing the right test at the right time in order to minimize WIP.

Long and variable lead times

In an attempt to be more productive, many laboratories build up queues of samples for tests with long set-up times (e.g., HPLC or GC). While some grouping of samples is a good idea, this is usually overdone and needs to be controlled in order to avoid long and variable lead times, equipment conflicts, and imbalance in daily analyst workloads.

Ineffective fast-track systems

Labs often attempt to address the unpredictability associated with long and variable lead times by developing a fast-track system to allow urgent samples to be dealt with separately. Typically, however, the proportion of fast-track samples increases over time, to the point of being unmanageable. In designing a lean solution, laboratories can increase the velocity of every sample, eliminating the need to prioritize. This may sound impossible, but it can and should be done. If it is done correctly, the amount of analyst effort required per sample does not change; samples simply spend less time in queues.

Lack of cross-skilling

Training gaps are sometimes attributed to high analyst turnover; however, lack of cross-skilling is often as much of an issue in laboratories with low turnover where staff members have become subject matter experts and are de facto dedicated to specific tests or activities. Labs tend to operate at extreme ends of a spectrum, whereby they are either mimicking Henry Ford–style mass production, with analysts repetitively carrying out the same tasks day in, day out, or they are like “craft producers,” taking a sample through its full testing schedule whether it is productive to do so or not. In most cases, the optimum resourcing will be in the middle, with each analyst having the capability of doing all of the testing, but carrying out defined combinations of tests that use their time well and reproducibly meet demand in the most productive way.

Muda, Mura, Muri: Lean laboratory pitfalls

The focus of many lean laboratory projects is almost totally on waste reduction (or Muda, to give it its Japanese name). Significant time is spent on valuestream mapping to highlight new “wastes” to work on; while some improvements are made, these are often not converted into meaningful overall performance improvement.This is no surprise; waste is easy to see and understand whereas the more challenging wastes of “Mura”—the waste of unevenness (volatile workloads) and “Muri”— the waste of overburden (imbalance in daily analyst workloads) are often ignored. These are more difficult to understand, but effective dealings with them will deliver significantly greater productivity improvement than will tackling waste alone; indeed, this will provide a context in which the benefits of waste reduction can be “spent.”

The recipe for success

The most successful lean laboratory projects tackle the “leveling” and “standard work” aspects first. The best foundation for a lean laboratory is analysis of historical data and forecasts, in order to understand the leveled demand rate of testing and resourcing so as to adequately meet this leveled demand rate. Successful leveling of a volatile load and mix will significantly improve productivity and/or lead time. The productivity improvement can be used to provide additional capacity or converted into a cost reduction.

The results

Depending on the focus of the lean initiative, results will be seen in productivity improvement or increased testing speed— but often results will be seen in both areas.

Fig 1: Measurable improvements based on recent lean projects

These measurable improvements (from laboratories that have recently completed lean projects) demonstrate what can be achieved.

Lab work is not the same as manufacturing, but lean thinking can and should be applied in the laboratory environment.

Our consultants can provide further information on the above and discuss any aspect of Real Lean Transformation, simply set-up a call today.