Ten Mistakes Of SPC InitiativesRai Chowdhary
|
Those who mistake activity for progress, and do not care to seek guidance - eventually end up on the one way street to failure.....Rai Chowdhary | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
Statistical Process Control is considered to be one of the tools that can be used by both Manufacturing, and Service organizations to deliver better quality to the customer. However, it is often misunderstood and misapplied. I will discuss ten frequently observed errors on the SPC journey in this article together with some tips on how to avoid the same. Mistake No. 1: It does not apply to us:
You will come across cases where management, and / or others in the company feel that their operation is too unique, or different, and therefore SPC is not applicable. Such beliefs may arise because of several reasons such as:
As long as there is a process to create an output, SPC can be applied. Philip Crosby, a noted Quality Guru said "All work is a process". If there is an output, we will need to find a way to measure it, otherwise it becomes difficult to gage how well the output serves the customer's needs. When we start measuring, data are collected - which can become the raw material for SPC. Mistake No. 1 - What You Can Do About It... Start with measuring outputs; most organizations find this to be the easiest place to start. Track the variation in outputs, and see how it behaves. Concurrently work with the customer to either obtain or develop requirements / specifications. Then compare the variation in your outputs to customer specifications. Let the data tell you if your process is stable (operating within expected control limits), and capable (well within the specification limits). Keep in mind, to become more effective - eventually you will need to begin tracking the leading indicators. Staying put with measurement of outputs (lagging indicators) is likely to keep you in the reactionary (fire fighting) mode, rather than making you proactive. Also read Mistake Nos. 3, 4, 5 Mistake No. 2: Thinking SPC is a panacea, and will eliminate variation SPC by itself cannot eliminate variation, neither is it a panacea for quality problems. It is one of many in the tool chest and can serve a very useful purpose - that of showing how much variation is naturally inherent to the process, and when special causes occurred if any. Variation occurs because of "Common Causes", and "Special Causes", mistaking one for the other leads to serious problems. Consider the case of this pump manufacturer - blaming late deliveries to customers on plant layout. The thinking was that product takes too long to make it through the factory, where as the real cause was absenteeism / employees reporting for work late on certain days of the month. Over 70,000 dollars were spent changing the plant layout, while the real problem could have been solved for almost no cost by some adjustments in production scheduling, and shift start times. Also read Mistake No. 7. Mistake No. 2 - What You Can Do About It... Setup a good tracking system and be aware that you will need to do more than just SPC. Once causes of variation are understood they will need to be addressed. Invariably there will be two types of causes found - common and special. Some of the causes will be self obvious, some will require further analysis using simple tools such as Check Sheets, Root Cause Analysis (RCA), etc. However others will need advanced tools such as Design of Experiments (DOE), Analysis of Variance (ANOVA), Hypothesis Testing, Response Surface Modeling (RSM) to name a few. Variation elimination will come only via removal and / or control of both - common and special causes. In many cases these will become projects that Corrective Action Teams may have to pursue. Management will need to be seriously involved to ensure RCA is done adequately, and corrective action projects get executed. Mistake No. 3: Confusing between Specifications and Control Limits Many times as data is collected and compared to the Specifications provided by the customer, it is thought that as long as the outputs are within the Specification Limits, the process is doing fine. Thus implying that the process needs to be within these limits. Quite often the Specification Limits are plotted on charts and the process is tracked with regard to the same. This is not recommended practice at all. Specification Limits do not reflect what the process is doing, or is likely to do, therefore do not belong on the Control Chart. . Mistake No. 3 - What You Can Do About It... Educate everyone that Control Limits are the Voice of the Process, where as Specification Limits are the Voice of the Customer. The two are independent, and different entities, as such they must come from different sources. Control Limits are calculated based on the data collected from the process - they are calculated using Statistical Formulae. When you see Control Charts, make sure to ask how the Control Limits were determined. Mention of anything but the use of process data (or something to that effect) should be a warning signal. Mistake No. 4: Creating Control Limits based on some one's judgment, or opinion Several times, as SPC initiatives are kicked off, team members get asked to put certain limits on the chart and refer to them as control limits. When such limits are wide they give the impression the process is operating in control. The reasons why such control limits may be put in place are many - one of which is fear. This stems from a concern that out of control processes will result in negative consequences, or will impair the individual's track record. Imposing Control Limits on processes cannot make them better, rather it creates misconceptions and deception. Mistake No. 4 - What You Can Do About It... If you are a manager, work to remove the element of fear; otherwise brace yourself to deal with "cooked" numbers and biased charts. These will only "look" good, however will cause enormous harm to the organization in more ways than one. Understand that Control Limits are established based on the data collected from the process, and need to have sound Statistical principles underlying the same. Shewhart's constants have been historically used to create Control Limits; these are provided at the end of this article for your reference. If you are an employee facing such a situation, you may need to
educate others about the basis on which Control Limits are
established. One argument you can present is if such limits are
decided based on opinion, then, we can have as many control limits as
there are opinions. Which limit or limits would be right? Mistake No. 5: Not allowing the process to operate naturally, and tinkering with it constantly When data obtained from the process seem to be unfavorable, an
attempt is made to make changes - with the belief that we can improve
the process. If by chance, the next data point is in the favorable
direction, it will reinforce the belief that the change is working, and more of
it is implemented. This improvement may or may not last,
and then data start going the other way. This leads to more aggressive changes,
perhaps other culprits are chased, and even people fired under the
assumption that they messed things up. This the cycle continues, with chance
variations, and knee jerk reactions - eventually resulting in totally
uncontrollable gyrations in the process. Few realize the extent of
distrust and morale damage this leads to. The conclusions of what comes
next are best left to
imagination. Complete overhaul of the plant's equipment, and or
management staff now falls in the realm of possibilities. Those at
the receiving end call it "Punish the innocent, reward the guilty". Mistake No. 5 - What You Can Do About It... First and foremost, understand that one of the underlying assumptions
in SPC is that each data point obtained is independent of the previous
one. This means that the process must operate in its natural state for
us to get a sense of how much inherent variation will be present. Making changes as the process works nullifies this assumption, and
begins to introduce bias. The rules of Normal Distribution (or
other applicable Distributions) cannot be expected to hold under such
situations. Mistake No. 6: Management stays at an arms length, and assumes Control Charts will do it all Every now and then, managements realize they need to do something different. An edict is issued to the rest of the organization, with the expectation that the dictums will be obeyed and implemented. This approach rarely works! Theoretically, employees need to listen, understand, and implement the initiatives Management is driving. Today, however, one has to "sell" the change. Doing otherwise means use of position power and force, which because of its abrasive nature can create malicious obedience. Once this stage is reached, the initiative is generally doomed. Far too many corporate leaders stay at an arms length from the tough work of driving change, and working with the troops. Over time, they get out of touch with reality, and live in a world of their own, thinking that SPC is being deployed, as evidenced by Control Charts that are being produced. It takes some time to discover no improvement has occurred, and the program gets buried like many of it's predecessor flavors of the month. Mistake No. 6 - What You Can Do About It... Get involved! Establish overall objectives for the program,
begin using SPC on key business metrics to set an
example. Use Statistical Methods in your decision making, and
involve your staff in an ongoing dialog on Analytical Methods, including
SPC. This is easy to accomplish by setting aside a block of time
during your regular staff meetings. More importantly
ask key questions about the program, it's deployment, training of key
personnel, and how the success of the program is being measured. Ask for a
diagnosis of the causes leading up to such variation, and what is being
done to address the same. Mistake No. 7: Mixing up common causes with special causes This is one of the easiest tripping points in SPC. I recall one of the
VPs of manufacturing for a leading chip equipment producer insisting that each and every defect on the
equipment shipped by the company be investigated and fixed. This
company made complex process equipment, with each machine using over
50,000 piece parts. There
were simply too many opportunities for defects, and the effort required
to chase everyone of them soon got bogged down. While the intent is noble, the means to
achieve it were terribly flawed. For any system or organization, current performance reflects:
All these together determine how the process behaves - by and large, in the absence of rare / special causes. In most cases, there are simply too many systemic causes (common causes) - which makes it difficult to say exactly what caused a given non conformance. Consider the gas mileage you get from your car. Many variables influence the gas mileage on a routine basis - and the variation may hover within a range of +/-15% (say) from a certain average value. Now, if one day the mileage was found to be lower by 30 or 40% all of a sudden, it is likely that there was a one of a kind cause that resulted in this occurrence. May be a the circus was in town, leading to massive traffic jams, or a very cold winter day where you had to warm up for a longer time, or maybe something is wrong with the car.
Now, on the other hand, if we observe the gas mileage to be
lower than average by say just 7%, we would be hard pressed to identify exactly what
caused this. Hazarding a guess can result in expensive
solutions such as taking in the car for a thorough overhaul, and the
results may be a hit or a miss. Mistake No. 7 - What You Can Do About It... Start using Control Charts the proper way. First collect data and establish control limits. If violations of control limits is found to occur, it indicates "Special Causes" may be present - these will need to be found and addressed. Then the Control Limits for the process will show variation that exists on account of "Common Causes", or "Systemic Causes". Such variation cannot be reduced unless the system itself is improved. Improving the system in most cases is beyond the control of process operators, and SPC teams. It is by and large a management function. Making changes to the "System" are much more difficult to accomplish, therefore pushing SPC teams to get these done without supporting them will create frustration. Management involvement in this is key for obtaining results, as is the realization that SPC is a tool that must produce business results. . Mistake No. 8: Not checking for data integrity, and measurement system performance Very often these essential and basic steps are ignored altogether. Data that lacks integrity has a devastating effect on any subsequent analysis and decisions. Consider the case of late arrival data from three different airline companies as shown below:
If you were to compute the average late arrival time you will find all have nearly identical performance. A closer examination shows Always Flying has one data point that seems way out of line. Now the question is how should we treat this data point? Keeping it in penalizes the good performance of Always Flying. If we decide to eliminate that data point, we can be questioned as to why? Secondly, consider the smallest recorded value in each case. For Timely Airways and Always Flying, it is 0, whereas Getaway air has a smallest value of 6. Further, in the case of Always Flying, the next higher value is 10. Does this point to something? Could it be an internal policy of Always Flying that dictates any delay of less than 10 minutes be considered as the plane having arrived on time? Additionally, what if the measurement system that has a total error of say +/- 5 minutes? You will not be able to discern any improvements / changes unless a change of 10 or more minutes is observed. Now any improvement smaller than 10 minutes will always be questionable. This has other important implications too. Any data that lie within a 10 minute band from the Control Limits will now be suspect. The control limits thus begin to lose their significance, and ability to detect out of control conditions. Mistake No. 8 - What You Can Do About It... Before you go too far with SPC, lay down ground rules on how the data shall be collected and analyzed. For instance, what will be the least count of the measurement system, and how much error in the system shall be acceptable. Often an argument will be presented that the measurement system has been calibrated, and that is the only performance check required. Don't fall for it. In addition to Calibration, you also need to know the Repeatability and Reproducibility of the measurement system. Other problems with measurement systems include Drift, Linearity, etc. All need to be understood and addressed properly. The total error in Measurement System should not exceed 10% of the "Specification Window". This will ensure that the Measurement System is crisp, and repeatable. Data integrity needs to include tests of outliers, checks for faulty / contaminated data, validity of data with regard to time and place, etc. The outliers test identifies data points that may be at unjustifiable extreme values; however this does not license one to automatically throw out such data from the analysis. Outliers need to be examined further to determine if there was an error in recording of data, or an unusual event that generated such data. If an outlier is found to be a genuine data point, you may want to include it in the analysis. Mistake No. 9: Lack of empowerment and trust of teams implementing SPC A common gripe with SPC Teams is that they are getting all this training, but when it comes to applying and living with SPC, management is uncomfortable letting the teams adopt the new methodologies. This is exacerbated by Mistake No. 6; Management Stays at an Arm's Length. As teams begin putting SPC in place, and allow the processes to vary, supervisors get quite uncomfortable - because not every unfavorable data point is being chased any more. Rather we are letting the process behave in it's normal fashion. This is very unnerving, since we are used to taking charge, and exercising control. What such control yields - is another matte - for the moment, action was taken and that is what counts. Mistake No. 9 - What You Can Do About It... Exercise empowerment - let the teams work. If you have provided the right kind of training and mentoring, let the teams work with SPC and allow the rules of SPC to operate. Interfering with the process not only makes matters worse, it sends the wrong message to the teams as well - one that says they don't count, and what counts is your opinion. If that was to be the case, what was the point in getting the teams up to speed on SPC anyway. Keeping hands off can be hard to do, especially if Managers / Supervisors have been close to processes earlier, and believe they know what needs to be done. Mistake No. 10: Inadequate provision for training and coaching / mentoring SPC is not something one can easily read from a book and expect to implement right away. Lack of training in the application of the tool and driving the initiative can jeopardize the whole effort. Take the case of Mistake No. 8 - Checking Data for Validity and Integrity. Hardly any book on SPC refers to this as a crucial step, and yet - when ignored it can have serious consequences. The few thousand dollars saved by avoiding (or going cheap on) training and mentoring in most cases ends up costing 5 to 10 times more eventually. When training is delivered, but it's effectiveness goes un-checked, we do not have any confirmation of whether the participants really learned anything. Mistake No. 10 - What You Can Do About It... Budget for training your associates, operators, SPC teams, professionals, managers and supervisors. Everyone will need to come on board, however the learning needs will be different for different groups. Supervisors and Managers especially will need to understand what SPC is, how it works, how decision making will change after SPC is implemented. They will also need to learn how to implement / drive such initiatives, and most importantly allowing the process to speak freely. Key questions to ask of SPC teams, and operators will be additional topics that can serve Managers and Supervisors well. Operators must know how to avoid mistakes in data collection and handling. They must also know the symptoms as exhibited by control charts to the extent that they have decision making authority with regard to process operations. Professionals and SPC teams will benefit from a thorough understanding of the Statistical Principles underlying SPC. Associated topics such as Root Cause Analysis, Process Mapping, etc. should not be ignored, since they often become excellent aids in identifying causes of variation. Also read Mistake No. 5 and 7 Concluding Remarks: I trust you found this article informative. Your feedback is very welcome - e mail me at rai_chowdhary@yahoo.com, or call: 1-877-HOWNWHY (1-877-469-6949). You may copy / print / distribute this article as long as the author is acknowledged, and the source of the article is referenced.
Last Updated: 2/8/05 Control
Chart Constants
|
SPC is one tool in the chest of Six Sigma
Tools; become a Six Sigma Professional through Certification
FMEA can be of great value
Design of Experiments can be of
tremendous value in pointing to those variables where SPC should be
used.
Understanding the customer is very important - that can identify the specification limits within which you want the process to operate. SPC benefits will be rather limited if the process operates outside such limits. You will gain consistency, but will be consistently wrong. Learn how to listen and understand the voice of the customer - with the right training from TEAM 2000
Regardless of the nature of your product, process, or service, variation will always be present. How much is allowable? For this you will need to do a proper functional analysis of the product / service, how it will be used by the customer, and how it will perform under diverse conditions of usage. Give your product / process / service a thorough functional checkup, we can help. Call / write us... Phone: 1-877-HOWNWHY, or rai_chowdhary@yahoo.com
Making decisions on what corrective action to implement can be tricky since many solutions can be used to resolve a given problem. How to prioritize corrective actions in the face of the numerous factors that have to be taken into account. Well there is a simple and effective technique you can use - Prioritization Matrices! If you would like a short session on Decision Making, we will be glad to provide the same. This can be done even during a lunch break or via distance learning with the web. Call / write...
Digging for the root causes can lead you
into a rat hole! Think before you begin, and know when to stop -
or else the hole will become a maze in which you can get lost. We will
be more than happy to be of assistance...all you have to do is call /
write.
When your executives need to decide on how to improve business operations we will be happy to be a valuable resource. You will get real world advice - not - academic ideologies. This we can provide because we have been in the trenches - running our own business; not once but on several occasions. We can be reached at 1-877-HOWNWHY, or
1-877-469-6949
When you get promoted to a management or executive position, you will need to change the way you work, and will need different skills to be successful. What are these skills, how will you acquire the same? We can be your coach and sounding board... Call: 1-877-HOWNWHY, or
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
