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During a Core Tools III training session I presented, a student asked a relevant question which deserves a quantitative answer. So to answer more comprehensively than I did during the training, I will break down my response to this question into several posts you can follow. Often in the automotive industry, we throw around phrases like “Best in Class”, “Lessons Learnt" and "Robust Process” without further explaining what we mean by these. I was asked “What is a Robust Process?” when using that last phrase. Having briefly answered what a robust process is without quantifying it, I continued the lecture. If someone had given me that answer when starting in process manufacturing, I would have again asked “So what is it?”. The definition is: A robust process is one that consistently produces products at the required volume and meets or exceeds the customer’s quality expectations with minimal variation regardless of changing conditions or inputs. That statement still leaves me asking the same question. It does not give me boundaries or targets to which I can claim I have a robust process. So let’s dig deeper. What do I need to achieve to make my process robust? This question should be asked when designing the initial process at your PFMEA stage. Unfortunately, all too often, this critical stage of process design is often overlooked. However if you have inherited an existing process that performs below expectations, then you need to identify the functions or systems that need to be initiated (if they don’t already exist) and the targets for each of these “Tools” in order to claim a robust process. If we look at the definition above, we can start to break it down into chunks... Firstly, if we want a facility to perform with minimal variation in the required volume, the production line must be capable of achieving quantity and quality. If quality is poor, this will have an adverse effect on both the quantity and delivery. So what better measurable to monitor than Overall Equipment Efficiency (or OEE in short)? Okay, I hear some ask, so "What is OEE, what is my target and what do I need to do to reach and maintain that target?". I am not going to do in these articles is teach OEE or any other system that gets mentioned, however, I shall give pointers and targets to such mentioned quality systems to help you understand what they are and, more importantly, what the quantifiable target values are. Hopefully having wet your appetite, my next article will break down what OEE is, what to aim for and what tools and systems help maintain OEE. Written by: Matthew Woodford (ht+a Trainer & Consultant)

Having explained in the first part of “What is a Robust Process”, I ended by saying that OEE is a good indicator of understanding the “health” of a production facility. Overall Equipment Efficiency (OEE) is a measure of the ability of a machine to consistently produce a product which meets quality standards at the designed cycle rate without disruption. World-class standards aim for an OEE of or above 85%. So what makes up OEE? OEE measures three key indicators - these are made up of other key measurable such as Dock To Dock (DTD), Build To Schedule (BTS) and First Time Through (FTT), but let’s look at the top levels which are: •       Equipment Availability •       Performance Efficiency •       Quality Performance Looking at these three key areas we can therefore express that: OEE = Availability x Performance Efficiency x Quality Rate Where AVAILABILITY is the amount of time the machine or process was available to run compared to the amount of time it was scheduled to run. Therefore: Availability = Operating Time / Net Available Time PERFORMANCE EFFICIENCY determines how closely a piece of equipment runs to its planned cycle time. This can be affected by speed losses and losses associated with undocumented idling or minor stoppages resulting from blocked or starved upstream or downstream equipment. If possible this should be logged if it is having an impact on key equipment performance efficiency. Therefore: Performance Efficiency = (Planned Cycle Time x Total Products Run) / Operating Time Finally, QUALITY RATE is the total number of good parts produced on a machine or operation compared to the total products run, or: Quality Rate = (Total Products Run – Total Rejects) / Total Products Run To summarise: a process should achieve 85% or more to be classed as a Robust Process. If you have attended the Core Tools training you will know that you can derive various data sheets to capture supporting data to help with the above. This blog is not about teaching OEE as such, but should further knowledge about OEE please consider our Manufacturing Excellence (Lean Manufacturing) training. Next, I will focus on quality performance indicators... Written by: Matthew Woodford (ht+a Trainer & Consultant)

APQP, FMEA and PPAP are all about designing all the controls and capabilities for a robust process. Trying to convert an existing poorly performing production facility into a robust process can be done but requires time (often downtime whilst trying to support production!) and extra cost. To do this would be a whole new conversation! Setting the scene... You have your new production line. It has been commissioned and has been producing good parts. Like a new car, it drives every bit as it was designed to do and delivers a pleasurable driving experience. But fail to do your quality inspections (oil, water, tyre pressure etc.) and that driving experience could change to a negative one quickly! Ignore the scheduled maintenance intervals and the reliability in performance will be compromised.  A production line, machines and gauges are no different. So what do we need to do to monitor and maintain our robust process? Naturally, everything is specified in our PPAP! But in this section, I want to focus on continuous improvement, SPC and MSA. Continuous improvement is driven by the philosophy of "if you’re not improving then you’re standing still". If you’re standing still in today’s competitive environment then you are actually going backwards. No matter how well the process has been planned, there is always an opportunity for improvement. There will be quality concerns - internal or external. There will be performance breakdowns. There will be information based on customer feedback, employee involvement teams, quality data analysis, market dynamics and technology improvements. So we can continue to build a better and more efficient production facility. There are several tools to assist in continuous improvement: Kaizen; PDCA; Six Sigma; Lean Manufacturing; Value Stream Mapping and SPC. Applying any one or more of these methods can help keep you focused on keeping your production facility robust. Let's split SPC or Statistical Process Control into two parts: Process Capability: As was discussed earlier, capability assesses the ability of a process or operation to repeat within predefined specifications, defining the variation of the process to that of the tolerance limits. We use the indices Cp/Cpk, Pp or Ppk to quantify how well the process meets drawing specifications. Process capability should be performed at least once every twelve months. Control Charts on the other hand are used to monitor the stability of the process over time. A typical Xbar and R chart plots the performance of the process over time against calculated control limits (not tolerance specifications). Using control charts helps identify trends, shifts, or other patterns that may indicate special causes of variation that require investigation and corrective action to keep the process under control. So we can say that capability analysis studies whether or not a process is capable of meeting drawing specifications, whereas control charts monitor the ongoing performance and variation of the process. Both are needed if we wish to maintain our robust process. As for MSA (Measurement System Analysis), we need to perform an analysis to ensure the measurements taken from a manufacturing process are both accurate and reliable. More commonly known as a Gauge R&R (Repeatable & Reproducible) Study, this ensures the equipment we use to obtain data that we do or do not act upon or make decisions about, is reliable, accurate and capable of producing consistent results. I hope I have succeeded in defining a Robust Process and the tools for measuring and maintaining a robust production facility. Till next time! Written by: Matthew Woodford (ht+a Trainer & Consultant)