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Manufacturing and Quality Perspectives article



หลักการกำหนดวัตถุประสงค์คุณภาพ ยึดหลักการ SMART คือ
1. S = Specific ระบุชัดเจน เจาะจง มีขอบเขตที่แน่ชัด ไม่คลุมเครือ
2. M = Measurable สามารถวัดและประเมินผลได้ คือบังคับกลายๆ ว่าต้องกำหนดเป็นตัวเลข 
3. A = Attainable/ Achievable สามารถบรรลุได้ ไม่เว่อร์จนทำไม่ได้ อันนี้เป็นบทเรียนของหลายๆ องค์กร
4. R = Realistic/Reasonable ตั้งอยู่บนพื้นฐานของความเป็นจริง มีเหตุและผล
5. T = Timeframe มีกรอบของเวลากำหนดไว้ ว่าเป้าหมายนี้ตั้งแต่เมื่อไหร่ถึงเมื่อไหร่

 A KPI can follow the SMART criteria. This means the measure has a Specific purpose for the business, it is Measurable to really get a value of the KPI, the defined norms have to be Achievable, the improvement of a KPI has to be Relevant to the success of the organization, and finally it must be Time phased, which means the value or outcomes are shown for a predefined and relevant period. 


Overall equipment effectiveness (OEE) is a hierarchy of metrics which evaluates and indicates how effectively a manufacturing operation is utilized. The results are stated in a generic form which allows comparison between manufacturing units in differing industries. It is not however an absolute measure and is best used to identify scope for process performance improvement, and how to get the improvement. If for example the cycle time is reduced, the OEE can also reduce, even though more product is produced for less resource. Another example is if one enterprise serves a high volume, low variety market, and another enterprise serves a low volume, high variety market. More changeovers (set-ups) will lower the OEE in comparison, but if the product is sold at a premium, there could be more margin with a lower OEE.
OEE measurement is also commonly used as a key performance indicator (KPI) in conjunction with lean manufacturing efforts to provide an indicator of success.
OEE can be best illustrated by a brief discussion of the six metrics that comprise the system. The hierarchy consists of two top-level measures and four underlying measures. 

Overall equipment effectiveness
OEE breaks the performance of a manufacturing unit into three separate but measurable components: Availability, Performance, and Quality. Each component points to an aspect of the process that can be targeted for improvement. OEE may be applied to any individual Work Center, or rolled up to Department or Plant levels. This tool also allows for drilling down for very specific analysis, such as a particular Part Number, Shift, or any of several other parameters. It is unlikely that any manufacturing process can run at 100% OEE. Many manufacturers benchmark their industry to set a challenging target; 85% is not uncommon.
Calculation: OEE = Availability x Performance x Quality
A given Work Center experiences...
Availability of 86.7%
The Work Center Performance is 93.0%.
Work Center Quality is 95.0%.
OEE = 86.7% Availability x 93.0% Performance x 95.0% Quality = 76.6%


First pass yield (FPY), also known as throughput yield (TPY), is defined as the number of units coming out of a process divided by the number of units going into that process over a specified period of time.[1] Only good units with no rework are counted as coming out of an individual process.
Also related, "first time yield" (FTY) is simply the number of good units produced divided by the number of total units going into the process. First time yield considers only what went into a process step and what went out, while FPY adds the consideration of rework.
Consider the following:
You have a process that is divided into four sub-processes: A, B, C and D. Assume that you have 100 units entering process A. To calculate first time yield (FTY) you would:
Calculate the yield (number out of step/number into step) of each step.
Multiply these together.
For Example:
(# units leaving the process as good parts) / (# parts put into the process) = FTY
100 units enter A and 90 leave as good parts. The FTY for process A is 90/100 = .9000
90 units go into B and 80 leave as good parts. The FTY for process B is 80/90 = .8889
80 units go into C and 75 leave as good parts. The FTY for C is 75/80 = .9375
75 units got into D and 70 leave as good parts. The FTY for D is 70/75 = .9333
The total first time yield is equal to FTYofA * FTYofB * FTYofC * FTYofD or .9000 * .8889 * .9375 * .9333 = .7000.
You can also get the total process yield for the entire process by simply dividing the number of good units produced by the number going in to the start of the process. In this case, 70/100 = .70 or 70% yield.
The same example using first pass yield (FPY) would take into account rework:
(# units leaving process A as good parts with no rework) / (# units put into the process)
100 units enter process A, 5 were reworked, and 90 leave as good parts. The FPY for process A is (90-5)/100 = 85/100 = .8500
90 units go into process B, 0 are reworked, and 80 leave as good parts. The FPY for process B is (80-0)/90 = 80/90 = .8889
80 units go into process C, 10 are reworked, and 75 leave as good parts. The FPY for process C is (75-10)/65 = 65/80 = .8125
75 units go into process D, 8 are reworked, and 70 leave as good parts. The FPY for process D is (70-8)/75 = 62/75 = .8267
The first pass yield of the set of processes is equal to FPYofA * FPYofB * FPYofC * FPYofD = .8500 * .8889 * .8125 * .8267 = .5075
Notice that the number of units going into each next process does not change from the original example, as that number of good units did, indeed, enter the next process. Yet the number of FPY units of each process counts only those that made it through the process as good parts that needed no rework to be good parts. The calculation of FPY, first pass yield, shows how good the overall set of processes is at producing good overall output without having to rework units.


The seven wastes: One of the key steps in Lean and TPS is the identification of which steps add value and which do not. By classifying all the process activities into these two categories it is then possible to start actions for improving the former and eliminating the latter. Some of these definitions may seem rather 'idealist' but this tough definition is seen as important to the effectiveness of this key step. Once value-adding work has been separated from waste then waste can be subdivided into 'needs to be done but non-value adding' waste and pure waste. The clear identification of 'non-value adding work', as distinct from waste or work, is critical to identifying the assumptions and beliefs behind the current work process and to challenging them in due course.
The expression "Learning to see" comes from an ever developing ability to see waste where it was not perceived before. Many have sought to develop this ability by 'trips to Japan' to visit Toyota to see the difference between their operation and one that has been under continuous improvement for thirty years under the TPS. Shigeo Shingo, a co-developer of TPS, observed that it's only the last turn of a bolt that tightens it - the rest is just movement.[4] This level of refined 'seeing' of waste has enabled him to cut car body die changeover time to less than 3% of its duration in the 1950s as of 2010. Note that this period has allowed all the supporting services to adapt to this new capability and for the changeover time to undergo multiple improvements. These multiple improvements were in new technologies, refining value required by 'downstream' processes and by internal process redesigns.
The following "seven wastes" identify resources which are commonly wasted. They were identified by Toyota's Chief Engineer, Taiichi Ohno as part of the Toyota Production System:[5]
1. Transportation
Each time a product is moved it stands the risk of being damaged, lost, delayed, etc. as well as being a cost for no added value. Transportation does not make any transformation to the product that the consumer is supposed to pay for.
2. Inventory
Inventory, be it in the form of raw materials, work-in-progress (WIP), or finished goods, represents a capital outlay that has not yet produced an income either by the producer or for the consumer. Any of these three items not being actively processed to add value is waste.
3. Motion
As compared to Transportation, Motion refers to the producer, worker or equipment. This has significance to damage, wear and safety. It also includes the fixed assets and expenses incurred in the production.
4. Waiting
Whenever goods are not in transport or being processed, they are waiting. In traditional processes, a large part of an individual product's life is spent waiting to be worked on.
5. Over-processing
Over-processing occurs any time more work is done on a piece than what is required by the customer. This also includes using tools that are more precise, complex, or expensive than absolutely required.
6. Over-production
Overproduction occurs when more product is produced than is required at that time by your customers. One common practice that leads to this muda is the production of large batches, as oftentimes consumer needs change over the long times large batches require. Overproduction is considered the worst muda because it hides and/or generates all the others. Overproduction leads to excess inventory, which then requires the expenditure of resources on storage space and preservation, activities that do not benefit the customer.
7. Defects
Whenever defects occur, extra costs are incurred reworking the part, rescheduling production, etc.

An easy way to remember the 7 wastes is TIMWOOD.
T: Transportation
I: Inventory
M: Motion
W: Wait
O: Over-processing
O: Over-production
D: Defect


NEWS AND INFORMATION ข่าวสารประชาสัมพันธ์ของเว็บไซต์, Love King, รักในหลวง article
Management Perspectives, มุมมองเกี่ยวกับการจัดการ article

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