Key Performance Indicators A vital tool in optimising the performance of your manufacturing system

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1 Key Performance Indicators A vital tool in optimising the performance of your manufacturing system Autor: Robert Gray Executive Summary It is a well accepted fact that the first step in improving (Or indeed controlling) anything is to actually measure it! All too often the very act of setting up a system of measurement can have the effect of making a system perform better particularly when people are an integral part of the process to be improved. By carefully selecting the correct key process performance indicators to measure and by understanding how each KPI interrelates to others, one can use these KPI metrics and clearly and concisely understand how a system is performing. This document will: Give you an outline of how such a Key Performance Indicators (KPI) system can be designed in the case of an SMT department. It will offer advice on how to structure such a system across multiple levels of an organisation to collectively align everyone in the improvement process. It will also suggest ways to instil high levels of personal commitment to high performance through a system of visual controls. Can be used as the starting point in your journey along the Build to Order improvement road. Other Build to Order best practice topic areas may offer greater interest to some engineers and managers however, I feel this one discipline of KPI is applicable to all and perhaps above all else offers the chance to achieve the most immediate and longest lasting improvement in the manufacturing system irrespective of its position in the Build to Order journey. 1. Who are the players? It has been said that the first step in making improvement is to measure. However, it is more productive to consider the first step as taking responsibility. When implementing a program of improvement it is necessary to correctly assign responsibility for improvement to the various people best located to effect improvement. These are the people day in and day out whose responsibility it is to operate the manufacturing system; - the production operators, front line technicians and supervisors. So, don t forget to engage, empower & energise the right people and make them feel responsible if you want to improve productivity. The production management and technical support staff are responsible to support all efforts in correctly operating the processes as designed, and to redesign the processes if given pertinent information suggesting such a change is necessary. 1

2 2. Where to start? One of my leading questions when performing a review of a production area is; - How do the production people know that they are doing a good job? I very often am greeted with blank stares in response to this question! Only when I suggest that perhaps when the production supervisors do not complain to the operators, then is that a sign that they are doing a good job that people start to appreciate the point. I go on to suggest that perhaps a better system could be that all the tasks and procedures an operator should perform in their day to day work should be explained and documented. (Standard work would be such a methodology and will be mentioned in a later paper on lean manufacturing) But just as important some key metrics should be established with graduated performance goals explained along with suitable escalation actions to be taken if those goals are not achieved. Along with this a method should be available to allow the production team to easily measure their performance against these key metric. A simple analogy could be; - When driving down the highway how could you know if you are speeding or not when there are no speed limits posted and no speedometer in the car? Should you simply wait for the flashing light to appear in your rear view mirror? The challenge in manufacturing has always been getting access to all the correct data, collating and processing this information to provide meaningful measurements on a processes performance, and to do this in a timely manner. So a successful KPI program collects the correct information, processes it in a meaningful and timely manner, and communicates it to the people best suited to effect change and control over the process. This communication method must be done in a way that enforces this feeling of responsibility and empowerment to effect improvement. So a successful improvement program must: Collect the right information Process the information in a timely and meaningful manner Communicate this information in an easy to understand manner Engage the production people as self actualising high performance teams In most of the factories which I have visited and where we have successfully implemented flexible Build to Order Concepts three main areas for performance measurement in an SMT department were considered: Productivity Process Quality performance Material control 2

3 3. Productivity Would you consider a production line to be operating effectively based on the fact that the machines are always running, or is there more to it than that? Take for example the graphic below showing a line with a high level of productive time of more than 94.9% In this case this was an effective line with very few assists and interruptions as shown with the blue and red areas of the graphic. However what if I then chose to disable half of the nozzles on each head, or slow down the accelerations for many of the components unnecessarily? The line would still show itself to be operational and have similarly high levels of productive time. However the actual output of the line would be significantly reduced. So clearly this KPI % productive machine state is not an accurate reflection of productivity and a higher level of productiveness is required. The main function of an SMT production line is to place parts on a PCB so a simplified toplevel metric for this can be the total number of components placed over a certain time period. 3

4 3.1 Average components placed per hour All other metrics are the result of factors that influenced this key metric, such as the ratio of productive time to scheduled productive time. The detracting factors for this KPI can be found in both the productive time of the line (How well a program is optimized for a line) and the non-productive time (Stoppages due to lack of operator attention, or changeovers, etc.) This is a relatively easy set of data to collect by simply collecting the number of components placed per hour and calculating an average for the time period under review. The above graphic is an auto generated report that provides many of the KPI and input to KPI for a placement line. From this graphic you can see the components placed over a defined time for average components placed per hour calculation, and also for an hourly view of this performance. By monitoring this it would be easily apparent if the line had changes made to it that slowed down the placement rate such as nozzle skips or acceleration restrictions. But also downtime due to maintenance, breakdowns, and changeovers can be observed allowing these issues to be controlled. Perhaps the only exception in the use of this metric as a KPI could be in the case of an NPI line engaged in extremely small batch NPI activities. In this case perhaps times taken for activities such as; setup and teardown, line changeover, first of verification, etc could be used as the KPI. However, components placed per hour may still be a valid sub KPI as it reflects the optimization off the line and therefore potential performance potentials when the product moves to volume production. 4

5 3.2 Process quality performance In a high mix environment one product may vary from another in a significant way, such as component complexity or component quantity. It is therefore not so easy to use product yield as a direct measure of process performance. For example, a product with 100 components will not have the same yield as a product with ten times as many opportunities for defects such as a product with 1,000 components. Similarly two products with the same component count will not have the same yield as another if the first only places 0603 devices and the other places components by a factor of four smaller such as devices. And from one time period to another, these product to product differences may have an effect on the overall yield even if the underlying core processes have not changed. Hence It is necessary to switch to a more proportional process metric such as one of the following; - Defects in proportion to opportunities o Defects per thousand components o Defects per million components o Defects per million opportunities Of course without a sophisticated set of automated data collection and analysis tools it would become very tedious to collect and collate all of this information for all production. Therefore it is suggested that a few high volume products are chosen and every week an activity sample of process performance is measured in order to establish a baseline and drive improvement. Of course when there is a chance to have direct feedback such as in line inspection then that is better and the use of statistical control tools also can aid in process improvement. In cases where in line automatic inspection machines are used then direct DPMO measurements can be made by correlating the components placed per time period vs. the defects found per time period. More details of how this KPI can be used in improving process quality will be discussed in a later article on Zero defects manufacturing. 5

6 3.3 Material Control Here we can use some basic metrics such as: Scrap per process stage in qty or value Material shrinkage rates Work order tact time through processes Directly at the SMT line we can also measure the identity and vacuum errors per station as this is a leading indicator for process quality and productivity in SMT. Additional benefits of actively tracking and controlling this metric are: There is less chance that a particular component shortage is encountered due to one feeder in the department wasting excessive quantities due to some avoidable process setting or corrective action. Even in the case where component pick up errors are slightly higher than normal this can directly effect the bottleneck cycle time of the placement process leading to underperformance in productivity. An interesting story about this metric in particular but also about how you engage with operators is; - Many years ago in a high volume OEM consumer products facility a new computer system for collecting pick up reliability data was developed and implemented by displaying on large CRT screens directly above the SMT line. (Yes it was that long ago!) This system replaced the paper SPC chart combined with the rather poor data reporting system at that time provided by the machine vendor that the operators had to complete regularly to control this key metric. I asked the operator at the line how was the pick up reliability of the line today? (Something they were used to me asking many times before) The response was; Oh! we do not need to take care of that any longer since the new computer system takes care of that for us now (As if there was some mystical OZZ type character behind the screen monitoring and correcting the process!) In their effort to make the operator s task easier someone had forgot to explain to them that even with the new system they were still responsible for this key process performance! And they must still know how they should monitor and control this process. It is only by ensuring that the operators are engaged in the process that we can have maximum advantage of their energy and diligence in controlling and improving the process performance. Additionally, in order to fully engage the production team they must also know how their performance on a particular issue effects and influences the performance of all other systems and the success of everyone at all levels. Therefore, it is necessary for them to understand across all levels the KPI and how each sections performance can effect and influence every other area. One method to illustrate this is by linking the KPI at all levels and areas to each other through a system of cascaded KPI. 6

7 4. Cascading the KPI In order to take advantage of measuring these KPI it is necessary to cascade the KPI across all levels of the system as shown in the diagram below. By cascading the KPI up and down the levels of the organization we can establish the importance of the metric and if the KPI is carefully selected its importance is relevant to all. In the case shown to drive productivity in SMT the average components placed per hour is used. In order to make this KPI relevant to the production team, only the average over time actually available for production is used, time due to material shortages or equipment breakdowns are excluded. By measuring at the department level an overall baseline can be established and long-term improvement goals can be defined. Certain projects and initiatives can be implemented at the engineering and management level to have an overall effect on this KPI. Any benefits from these projects can be visually demonstrated on the KPI charts, and the improvement success can be celebrated by all enhancing the overall team moral. By measuring at the Shift level the performance of each production shift can be compared to another. If significant differences occur then analysis can be undertaken to find ways to raise all shifts to the highest performing level. This can serve to act as a communication aid between managers and shift leaders; production and engineering support, and even between different shift teams to positively encourage competitive improvement. 7

8 By measuring at the line or team level the metric and performance can become personal. The individual as well as the production team can see directly how their performance cascades up and affects the overall KPI metric. Here again comparisons can be made between teams to search for ways to positively encourage competitive behaviour and improvement. This system of review and dialogue at all levels and between levels should serve to energize and drive improvement in a positive manner. The use of simple and clear visual control systems can serve to enhance this process. Going back to the point about responsibility one of the most powerful tools available to ensure people feel responsible for their own performance is to simply ask them personally to hand write on a large white board how they are performing. The fact that they personally are recording for all to see how they are performing against clear targets reinforces the feeling of responsibility instilling a sense of pride when achieving good results and a desire for improvement should the performance is below par. We can take, for example, the graphic of a large white board communication aid often used in SMT (But Visual controls will be another topic that we shall touch on later in greater detail). By the careful selection of KPI, implementing a cascaded system of performance measurement and improvement goals, combined with visual management programs it will be possible to develop an energised and driven organisation well prepared for the improvement programs that will be mentioned in subsequent articles that are essential elements of a build to order system. I hope I could give you at least the first few helpful suggestions for implementing a KPI system. Why not take a moment to review your own KPI methodology and consider if your manufacturing system is ready for the next step in developing a modern Build to Order capability? 8

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