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Testing-Testing-Testing: really important, but only a small piece of the process necessary to achieve the outcomes you are after.
It's unimaginable how much the world of manufacturing has changed in just 2.5 months?
Just 2.5 short months ago, our clients were looking to maximize OEE, maximize production yields while working tirelessly to reduce the cost per part manufactured.
Today is about quickly implementing new processes into our manufacturing environment, like social distancing and contact tracing to keep our work force safe, while at the same time slowly restarting our plants in a very uncertain market place.
Restarting plants amid so much uncertainty, is a huge challenge.
Uncertainty about the market: Is there going to be a customers that buy my product,
Uncertainty about the work force, Are my workers going to feel safe enough to return to work?
Uncertainty about cash flow, do we have enough resources to weather this storm no matter how long it lasts?
It’s a massive challenge for any plant, but the ones that I think are going to be most challenged?
The ones that have historically relied too heavily on tribal knowledge to manage their processes.
Plants that used past practices vs data to drive their day to day activity.
These are unprecedented times, and therefore relying solely on past experience is dangerous and puts people and business at risk.
Conventional wisdom doesn’t work in unconventional times.
To me, the only gut feeling we should trust right now, is the feeling that data and data analysis will be the only way to navigate ourselves safely out of this mess.
We’ve heard testing, testing, testing, over and over, but the reality is, testing is only one piece of the whole process that needs to be implemented.
We need to validate and verify, we need to interpret the data and take action, we need to learn and adjust.
The plants that have Plan-Do-Check-Act baked into their culture will be able to quickly implement the new processes and adjust their current ones to deal with the dramatically different lead metrics that are racing towards us.
Plants that respond to this crisis by plugging these new processes into a PDCA Management system is essential if we hope to emerge better, stronger, more efficient and less wasteful.
This crisis requires the Wisdom gained through robust data analysis and timely corrective action, not tribal knowledge or assumptions based on past experience.
So who’s going to thrive and survive as we come out of this?
The plants that can quickly implement new processes, quickly identify the new KPI’s that need to be integrated into their Plan Do Check Act management strategies, ie the ones that make data driven execution part of their core DNA.
Over-processing: when more value is added to a product than the customer actually requires.
By adding work that is not required, Over-processing costs money with regards to the time of staff, the materials used and the wear on the equipment.
By definition, for preventative measures to work, you have to be over-processing.
An example of over processing is when companies use aggressive PM programs to manage their systems.
When time instead of condition is used to change out their washers, rinse tanks, coolant sumps or oil systems.
When there is no cost effective way to identify and track end of life, then plants are stuck using wasteful preventative measures, however when the KPI's that do impact performance can be tracked and monitored, then condition monitoring lets you not only eliminate wasteful over processing, but it provides the data necessary to make better decisions moving forward.
By adding work that is not required, Over-processing costs money with regards to the time of staff, the materials used and the wear on the equipment.
These costs can amount to a considerable sum over a period of time, they will also reduce efficiencies as the operators that are Over-processing could be performing other value adding tasks that the customer is actually willing to pay you for.
In our world we see a lot of over processing that results from trying to contain problems.
When the lead KPI’s are not be controlled, companies are forced to be preventative, using past events and tribal knowledge to build PM schedules in their effort to avoid events..
This leads to significant waste and wasteful activity.
In this example, the source of over-processing identified was a final parts washing process.
The facility had installed this washer in an effort to address a part cleanliness issue they were having.
By running all the various components cleaned by 4 upstream washers, they used this final wash process as an extra level of insurance to minimize the risk of a quality event.
It increased costs, increased WIP inventory, consumed valuable floor space, required staffing etc. but if it meant they weren’t experiencing a “customer detected quality event”, it was worth it.
The problem was that this containment action didn’t address the real issue and repeated quality spills meant they had to look at the problem from a different perspective.
In most circumstances, all the KPI's are not known ahead of time, but by implementing a standardized approach to data collection and correlation, its possible to move from preventative to condition based in most systems.
And the move from preventative to condition based is essential for companies looking to get world class.
Caught in the Reactive Cycle, where the maintenance department is celebrated for repair instead of prevention and control, this data driven executive had to take some dramatic action to prove that things needed to change.
Changing how people think, what they prioritize and what they do every day is brutally hard.
But its necessary when plant culture stands in the way of reaching our World Class Goals.
What have you seen or done to try to encourage and drive culture change at your plant?
How have you demonstrated the consistency, commitment and courage necessary to make a lasting change in how people approach their work every day?
Please add to the conversation below.
We all want to learn how best to shift the thinking of our team if we are to reach our goals together.
Well....that depends, do you have the time and experience necessary to make the perfect chicken? Or are you trying to cook thousands of chickens, day after day, with people that don't have grandma's care or expertise.
Check out the video. Its an analogy we are trying to make comparing cooking chickens to producing thousands of identical parts at a world class manufacturing level, 100% quality, 100% on-time, at the lowest cost per part possible.
The more sites we visit, the more processes we audit, the more we see that variability is truly, in the words of Jack Welch, "the root of all evil". Process variability is what causes plants to have to build safety factors into their systems. And as these safety factors build over time, we see that they just continue to add to the cost per part and though they reduce the number of occurrences, they don't eliminate them, because the actual root cause to the problem is never identified or truly understood.
In this video, we reference a case study that documents how safety factors get built into processes as manufacturers try and keep problems from occurring , when they don't have the time, resources, systems or expertise to truly understand root cause. In this case an entire final wash process was added to the part flow in an effort to produce 100% quality. Even though the existing process was producing parts that met spec, "most of the time", non-spec parts occurred often enough that the plant had to do something to contain the problem.
Here's the issue though, not only does the extra wash process require added capital, operating costs, maintenance, increased processing time, process bottlenecks etc, it never addressed the actual root cause. So while it improved their quality yield, it still did not let them reach their 100% target.
If you are interested in reading more, follow this link to CI-222
It has always been amazing to me, how different disciplines in engineering approach problems from a completely different angle.
In this example, a mechanical engineer talks about their definition of a process in control, vs a chemical engineer's definition.
Now in parts manufacturing, the definition of perfect control, is zero variability in the part being manufactured. Once a standard has been set, the goal is 100% quality, meaning 100% of the parts manufactured meet that standard.
And whats the best way to reach 100% Quality?
Take as much variability out of all your process as possible.
Due to the nature of the types of processes Mechanical engineers tend to design, they look to "engineer out" variability. They look to build processes so robust that they are set and forget. Set them up once and then let them run.
Chemical processes however tend to be more dynamic in nature. Process inputs like flow, pressure, temperature, concentration, pH etc. can change quickly and significantly. Therefore when a chemical process is considered in control, its being sampled, analysed, interpreted and corrected on an on-going basis. Its constantly being monitored and maintained in its efforts to deliver 100% quality.
It is our contention that most of the processes in a parts manufacturing environment are mechanical in nature. These are the core processes. The processes where the company has the in house expertise necessary to control the aspects that impact product quality. The core processes are where these firms look to build their competitive advantage and innovate.
The problem is that there are a small percentage of the processes that are more chemical in nature than mechanical. These need robust process control solutions vs the more stable processes mechanical engineers are used to dealing with.
So where does Zimmark come in?
We are a bunch of chemical engineers that bring a unique chemical engineering approach to a predominantly mechanical engineered world.
We focus on the non-core chemical processes where inputs like pH, concentration, alkalinity, etc can all have a detrimental impact on part quality or total process cost.
By bringing a unique perspective and focus, we can help parts manufacturers reduce their costs and improve their OEE.
Curious if there is an aspect of your manufacturing process that needs a chemical vs mechanical mind set?
An area where maybe not all the process inputs have been identified and their variability is the root cause to aspects hurting your OEE?
Zimmark's Process Variability Audit looks to identify control problems in some of the processes that may not be on your radar as the root cause to quality, availability or excessive cost/waste problems.
Where there's smoke, there's usually fire, so a process where the inputs are highly variability can often be the source of the problem silently impacting plant OEE.
Sign up for your Process Variability Audit today, to find out if a bunch of chemical engineers can help you keep variability out of your manufacturing process.
A Manufacturing Oxymoron: Wasteful KPI's
How can a KPI be Wasteful?
Isn't the very definition of a KPI or Key Performance Indicator, a lead metric that helps drive the results we are looking to achieve in a manufacturing environment?
Though data and KPI's are the critical ingredient we need in order to optimize our processes and reach World Class Manufacturing standards, when they no longer change our behavior, they become a source of waste, not control.
Too many plants collect KPI's but don't do anything with them.
Too many programs have been implemented, don't sustain over time and no longer bring value and drive control or CI.
Look critically at your plant activities, look for the data acquisition tasks that are no longer bringing value, and either re-commit, or stop doing them altogether.
Just like the CEO that called his Lean Team Boards "Window dressing" because they didn't change the process or what people did every day, in our relentless effort to eliminate waste and wasteful activity, we need to either fix our data driven initiatives, or stop doing them.
So the question, what Lean initiatives are you going to either stop doing altogether or instead decide to recommit to?
After our last Post "KPI or Useless & Wasteful Metric?" we received a great story from one of our clients.
After touring the CEO through his facility, and proudly showing off the Team Leaders Metrics Boards, the CEO asked him the tough question: "what process changes have you made from all this data that will add value and get more product out the door?”
After some reflection our young plant manager couldn't honestly come up with any direct examples of how the data had improved the process or increased their OEE.
To that the CEO said: “if you are not doing anything to add value with the data, it’s just Window Dressing!”
Using data to change behavior is tough, tough to establish but even tougher to maintain.
There are many reasons it fails, many reasons that over time data moves from an agent of change to wall hangings that fill up plant production boards.
We are looking to compile and add to the list of why data can go from change agent to window dressing, and need you help.
Help us all avoid those potential pitfalls by sharing a time at your facility where the data was being used for a while to drive OEE improvement, but over time, it just turned into window dressing.
Any stories you could share that highlight that switch from value to waste would be greatly appreciated and benefit us all!
Thank you for sharing!
Only one way to find out.
Sometimes what seems like useless data, data that’s not worth collecting, not worth analyzing and not worth reviewing can in fact lead to Insights that can have a significant impact on a manufacturing facility.
They can become an important lead metric.
Watch this video for what happened.
It's about a facility that needed to address an urgent issue but didn’t think that collecting related data was worth the time or effort.
Knowing what data to collect can be a challenge, because unless you collect timely and reliable data and then take the time to interpret and look for relationships to performance results, its useless.
Data only becomes valuable if it can be turned into information that changes behavior that leads to a desired result. Data for Data’s sake is useless.
But we know that data driven execution is the only way to optimize any process. And process optimization is the name of the game in manufacturing today.
Every manufacturing plant has hundreds of unidentified lead metrics, hundreds of un-managed variables that are slowing the progress to World Class.
What lead metrics are you focused on 2019? Are there lead metrics you are not even aware of yet?
Identifying Lead Metrics and then managing their variability to minimize costs/impact on the manufacturing process is essential if process optimization is the Goal.
Zimmark's World Class Process Variability Assessment is designed to determine if process variability is hurting plant OEE or plant profitability.
Its focused on determining if the metrics that are not currently part of your control plan, are in fact standing in the way of meeting your goals.
Are those un-managed variables, the lead metrics that are standing in the way of sustainable process improvement?
For more information go here.
Sometimes Data alone is just not enough.
You need to take a stand.
Check out this story about a site where our supervisor made a stand in order to get the support he needed to fix the root cause.
A 100% reduction, that's Impact!
A neat story from one of our clients., that I think illustrates the point beautifully that sometimes data alone isn’t enough, sometimes it requires taking a stand to make a change happen.
At this parts manufacturer, we manage all their lubrication systems.
And with over 150 hydraulic systems alone, this facility generates hundreds of data points each day.
One of the many tools we use to help prioritize what all that data is telling us is something called Consumption Alerts.
Their job is to highlight and identify changes in how much oil a machine is consuming.
Their job is to help shine a very bright light on the machines that are:
1) Starting to consume more and more oil
2) The machines that are At the greatest risk of running dry and impacting plant OEE
3) The machines that are requiring the most attention due to increased inspection frequencies and top-ups.
But even with the very best alerts, it can seem like noise to a maintenance department that is working hard to keep their core processes up and running.
Getting their attention is tough.
So when the rate of consumption of a specific machine crossed new alert thresholds, our site supervisor knew he had to somehow escalate the issue.
He didn’t want this data, this information to be lost within all the other pieces of performance data being fed to the maintenance department on a regular basis, so he decided he needed to take a stand.
By Camping out in the maintenance managers office until he was assigned the necessary maintenance resources, he was able to communicate the importance of repairing this non-core aspect of the operation.
Now fortunately he had a good relationship with the maintenance manager, fortunately he had credibility by only using this strategy for high priority events, and fortunately it only required ½ hour to identify and make the repairs, but since making that stand, not a single drop of oil has been added to the system.
The data was there, it was at the top of the list, but until something occurred that broke the pattern, this leak would have continued to worsen.
Fortunately what broke the pattern was a proactive event, the stand.
Too often change only occurs following a reactive event, a major failure that would have resulted in a production interruption and major equipment rebuild.
So my question to you is, where in your plant do you need to take a stand. What process do you know is broken, but will be ignored until there is a major issue or event where its the root cause?
The rewards of letting data vs events drive your actions are immeasurable, but it requires rigor, it requires discipline and it requires courage.
It requires taking a stand.
Opinion is dangerous. Opinion leads to non value add activities. It leads to waste and wasteful activity. It leaves the facility vulnerable to quality problems putting the people and process at risk of an un-managed event.
I was visiting a plant this week that was struggling to consistently meet its quality spec. When we talked about their investigation process it became obvious that opinion not data was driving their decision making.
Opinion from operations, opinion from quality, opinion from maintenance, opinion from management.
Everyone had an opinion, the problem is, no one had data.
So what was decided?
They decided to address the problem by adding a step to the process.
Adding a final stage that was meant to address the thing that was causing the part to fail its quality check.
Now sometimes in the complete absence of data, you are left with only one option, your very best guess.
Everyone shares their opinion, you look for what sounds the most reasonable, has the most consensus and you implement.
Unfortunately, guesses stack upon one another.
They build over time and they create a culture of opinion instead of a culture of data and continual improvement.
World class companies drive opinion based decision making out of their plant.
They focus on building the systems necessary to identify, collect and interpret the metrics and analytics necessary to make decisions based on KPI’s not opinion.
True Data driven decision making is tough, it requires discipline, robust systems and relentless interpretation of the data, but it’s the only way to drive continual improvement and the systematic elimination of waste and wasteful activity.
If opinion and things like time based PM’s drives your culture and your activity, the good news is there’s a step change opportunity available to improve both your OEE and your profitability.
The bad news is it requires a change in culture which can be a daunting task.
If culture change is what you’re after, if you’re frustrated that opinion is driving costs and activity at your plant, then message me and we can start a conversation on how we can help shift the culture at your facility.