Leaderboard

A limit is the optimal value which is allowed. In order to achieve a stable process and capability in six sigma, control limits and specifications limits are widely used. Control Limit(CL) and Specification Limit(SL) are mathematical restraints unlike sky is the limit which know no boundary. However, both have different applicabilities and vary completely in terms of concepts and statistical perception. Essentially, CL is the voiceprint of the process which act as an indicator to apply actions in a process. It is computed based on measured data population which is presented on Control Charts. Usually an X-bar chart is used for representation. Such values are then attributed to subgroups to reveal the performance of the controlled process. These limits are set at the center of +/-3(sigma) such that the center and the sigma are enumerated according to the selected control chart. It exist 2 types of CL being Upper Control Limit(UCL) and Lower Control Limit(LCL). In simple terms, UCL is obtained by adding the mean with 3 times the standard deviation(s.d): (Mean + (3*s.d)). On the other side, LCL is obtained by deducting the mean with 3 times the s.d: (Mean - (3*s.d)) An illustrated X-bar where the specifications fits into the control limits is shown below. SL is the voiceprint of the customer which acts as a law maker to produce what the process really have to materialized. It is designated by the customer with regards to the characteristics set out which is presented on Histograms. Probability and box plots are also used for representation. These values are attributed to items rather than subgroups in order to unfold the good items away from the bad one. The Upper Specification Limit(USL) and Lower Specification Limit(LSL) are the 2 types for SL. USL and LSL are used to gauge the level of customer demand. If the item fits the range of the limits, then the item is considered to align with the needs of the customer. Else, if the items is out of range, the item does not comply with what the customer expected. A vivid representation of SL using histogram is illustrated below. To have a clear picture of CL and SL, let’s take a look upon the relationship between these two. If the CL fits into the specifications, then it is indeed the top notch design for an organization process. This is so because any variation emanating from known source will fit into the specifications range. In such situation, even if the CL vary over a period of time, it will not sever alarming consequences to render the customer specifications as required. If the CL is equivalent to the SL, then all variations which are known from the process will definitely align with the specifications of the customer. The major stumbling block in this situation however will be to make the process undergo statistical control due to the appearance of any unknown variations will result into defects. If SL fits between CL, there will a portion of the process that will cause dysfunctional operability. When the CL surpass the SL, some process will be operating beyond the specifications quotas. In other words, having CL larger than SL will without a doubt lead to the creation of defects. If there exist no linkage between LSL and USL, it is clear enough to conclude that the whole process is unfeasible with regards to the specifications meaning that the process itself is defective. This can happen whenever the design of the process is by all means incapable to unite customer specifications. It can happen that the process is behaving correctly but the expectations from the customer is erroneous or the process has triggered highly deficient issues from the design being incapable to meet what the customer expected. A simplified scenario presented below to better understand how CL and SL is being applied winning a pizza competition. Panecuit is a known pizza maker in Paris who wants to compete for the international best pizza in Italy. He looks out for the best Chef in Italy to gave him a helping hand to compete against the other participants. The Chef gave him the records of the top performance statistics and provide him with valuable piece of information. The key to reach the pinnacle to win is to complete the pizza within the timeframe of 20 seconds(sec) to 25 seconds. It is within that range that the preceding competing participants won the competition. Without any further do, Panecuit get holds unto practicing and begin countdown his performance. Under his scrutinize monitoring of performance, his range of having a pizza into the oven is between 22sec to 30sec, considering that deviation of 3 sigma with respect to the mean performance. At that time, 20sec to 25sec was the objective to be achieved while 18sec to 26sec was the current performance. One important factor to be taken into observation. CL is primarily used to analyze variations arising out of performance. Even Panecuit’s performance ranges from 18sec to 26sec, it still pose a matter of concern for the competition. The other participant, Cuitlente, might present a steady performance which will make him stand out as a winner. He is performing with a countdown ranging from 20sec to 24sec having an identical mean of performance as Panecuit with 24sec. What is to be noted here, is that Cuitlente clearly shows to be more consistent and display few variations and thus preference will be given to Cuitlente rather than Panecuit. Let’s introduce Cuitvidé, with a consistent CL of 20sec to 22sec. Cuitvidé showing clear sign of constrict variations and more consistency within the timeframe, that is the specifications area. Hence, he will stood at a winning advantage as compared to the remaining.