Bhisham C. Gupta - Statistical Quality Control

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STATISTICAL QUALITY CONTROL
Provides a basic understanding of statistical quality control (SQC) and demonstrates how to apply the techniques of SQC to improve the quality of products in various sectors Statistical Quality Control: Using MINITAB, R, JMP and Python
Statistical Quality Control: Using MINITAB, R, JMP and Python

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7 Tree diagram: A visual tool that breaks broad categories down into finer and finer levels of detail, helping to move step‐by‐step thinking from generalities to specifics.

2.4.2 Lean Tools

Recently, the Six Sigma methodology has been enhanced by incorporating the tenets of Lean Thinking . The Lean philosophy places importance on mapping the value stream and stresses the elimination of waste and continuously improving processes. Lean tools such as Eight Wastes, visual management, the 5S method, value stream mapping, mistake‐proofing, and quick changeover have become powerful tools used in the Improve and Control phases of Six Sigma projects. Together, Six Sigma and Lean deliver higher quality, increased efficiency, and flexibility at a lower cost.

The Lean philosophy follows five principles. First, we specify value, as perceived from the end user’s point of view. Next, we identify the value stream, which includes all the activities performed from the time of customer order to delivery. Every task we perform can be classified as value‐added or non‐value‐added. Third, we create flow so that our product – parts or paperwork or information – moves through the system without any hiccups. Fourth is the idea of pulling from the customer, meaning that we will make a product when a customer orders it, as opposed to making products that sit in inventory. Finally, we seek 100% quality and perfection in our operations. Contrast this to the Six Sigma goal of 3.4 DPMO, which is the result after the 1.5σ shift. The Lean goal of perfection lends itself to the idea of continuous improvement: we can always do better; we are never done; we will never quite reach the goal.

Non‐value‐added activities or policies are classified as waste . In Lean, there are Eight Wastes, and the goal is to identify and eliminate this waste. This contrasts with Six Sigma, in which we try to reduce variability.

2.4.2.1 Eight Wastes

As we have noted, the emphasis of Lean is on reducing waste, and there are eight named wastes: t ransportation, i nventory, m otion, w aiting, o verproduction, o ver‐processing, d efects, and s kills (TIM WOODS). These wastes do not add value to the product or service and should be eliminated. We’ll now define each of them.

Transportation waste is the movement of things, whether actual materials, paperwork, or electronic information. Moving things from place to place does not add value to the product or service. In fact, there is a higher probability of parts getting lost or damaged, the more we move them. There might also be delays in availability because objects are in route. This may lead to another waste: waiting. One of the causes of this type of waste may be poor workplace layout.

The next waste is inventory . This waste describes an excess of things, whether it is parts, supplies, equipment, paperwork, or data. Accumulating and storing inventory costs money, so a major effect of this waste is reduced cash flow. We may lose production because we are looking for things in our disorganized storage areas, and inventory may get damaged or become obsolete before we can use it. We know we have excess inventory if there are stockpiles of materials or messy storage areas. The root cause of this type of waste is a just‐in‐case mentality, which might also be driven by an unreliable supply chain.

Next is the waste of motion , which is the movement of people, in contrast to transportation, which is the movement of things. Often these two wastes occur together, since it is likely that people are moving the materials around. Motion waste could stem from a poorly designed process, where operators must use excessive motion to get their jobs done. Motion waste may result in worker injury.

Waiting waste occurs when people wait for other people. This waste is incurred when meetings start late, when people must wait for information before they can move on to the next step, and when people wait for products or machines to be available. We can also think of this waste another way, in which information, products, or machines are waiting for the people to act upon them. Waiting increases cycle times and may increase overtime hours. It can be due to unbalanced workloads or a push environment, where products are sent downstream even if the next process is not ready for them.

Next we have overproduction waste. A direct consequence of overproducing is inventory waste. It can also trigger waiting waste for work‐in‐process parts.

Over‐processing waste is doing more than the customer is willing to pay for. This waste includes performing inspections. The customer is not willing to pay more for inspection; they expect the product to be made right in the first place. Over‐processing waste could also be incurred by adding features to a product or service that are not valued by the customer. This type of waste may result in longer lead times for delivery and a frustrated workforce that is asked to do tasks that are not adding value.

Of course, a major contributor to waste is defects . When we have defects, we increase internal and external failure costs and create dissatisfied customers.

The final waste is the waste of skills . This is the waste of an organization not using employees’ aptitudes to their fullest extent. This waste can result in frustrated workers, absenteeism, and turnover.

There are many interconnections among the various forms of waste. When there is transportation waste, chances are there is also motion waste. If these two wastes exist, there might also be waiting waste. Overproduction leads to inventory waste, and so on. Many of the root causes of these wastes also overlap. For example, lack of training is a root cause for transportation, motion, waiting, defects, and skills wastes. Root causes for each of the wastes are summarized in Table 2.2.

2.4.2.2 Visual Management

A major tenet of Lean is visual management , a technique that makes the current status of inputs, outputs, or the process readily apparent at a glance. In general, visual‐management techniques are inexpensive, simple, unambiguous, and immediate. By using visual management, problems are easily detected and so can be corrected quickly.

Visual management tools are often low‐tech, such as using colored tape on the factory floor to show where inventory belongs, where someone shouldn’t stand, or where fork trucks will be traveling. Racks and bins can be color‐coded by part type. Indicator lights on machines can be used to signal run status, and pictographs of work instructions allow operators to easily reference process steps. Maintenance charts can show the latest service performed, and statistical process‐control charts show the current process performance. Visual management can certainly be used in a manufacturing plant, but it also can be used in an office, hospital, restaurant, or any type of workplace.

Table 2.2 Root causes of the Eight Wastes.

Waste Root Cause
Transportation Poor layout Lack of cross‐training
Inventory Just‐in‐case mentality Unreliable supply chain
Motion Poor layout Lack of cross‐training Insufficient equipment
Waiting Too many handoffs Push environment Unbalanced workloads Lack of cross‐training
Overproduction Lack of systems thinking Push environment Individuals valued over teams
Over‐processing Lack of trust Unclear customer requirements
Defects Poor training Non‐standard work Lack of job aids Poor communication
Skills Lack of trust Lack of training Silo thinking

2.4.2.3 The 5S Method

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