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Chapter 31: Problem 25

The computer makers who buy monitors require that the monitor manufacturer practice statistical process control and submit control charts for verification. This allows the computer makers to eliminate inspection of monitors as they arrive, a considerable cost saving. Explain carefully why incoming inspection can safely be eliminated.

Short Answer

Expert verified
SPC and control charts ensure process stability and quality, eliminating the need for additional inspections.

Step by step solution

01

Understanding Statistical Process Control (SPC)

Statistical Process Control (SPC) involves using statistical methods to monitor and control a process. This ensures that the process operates efficiently, producing items that meet quality standards with minimal variation. SPC is crucial for identifying and correcting variances before they result in defects.
02

Analyzing Control Charts

Control charts are tools used in SPC to plot data over time and determine whether a process is in statistical control. They help in identifying trends, shifts, or any unusual patterns that could indicate a problem. These charts include control limits that define the boundaries of accepted variation for the process.
03

Evaluating Consistency and Process Control

When control charts consistently show that a process is within control limits, it indicates the process is stable and capable of producing consistent quality. This reliability means that the items produced will have minimal variation and defects. As a result, confidence in the quality of the output increases.
04

Eliminating Incoming Inspection

Because of the demonstrated process stability through control charts, the producer can assure the quality of the monitors. This eliminates the need for the computer makers to perform additional inspections, thereby saving costs. The trust in the manufacturing process replaces the need for inspection of each shipment.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Control Charts
A control chart is an essential tool used in Statistical Process Control (SPC). It's like a traffic signal for quality assurance. By plotting data points over time, control charts help in monitoring the stability of a process. The main components of a control chart are:
  • Center Line (CL): It represents the average or mean value of the data.
  • Upper Control Limit (UCL) and Lower Control Limit (LCL): These are boundaries set at a certain distance from the center line. They indicate the acceptable limits of variation in the process.
Whenever a data point falls outside these control limits, it's a signal that something unusual is happening. This might be a glitch in machinery or a need for human intervention. Thus, control charts play a crucial role in ensuring the process remains stable and predictable over time.
They help manufacturers produce items that meet quality standards without extensive individual inspections.
Process Stability
In the world of manufacturing, process stability is like a promise of consistency. It means that the process consistently produces outputs within the specified limits.
A stable process is reliable, as it reduces surprises and defects, which are vital for maintaining product quality. Process stability is achieved when:
  • All data points fall within the control limits.
  • The process shows no signs of special-cause variation, such as abrupt shifts or trends.
  • The process variation is only due to common causes, which are predictable and manageable.
When a process is stable, it ensures that the manufacturing outcome is dependable. This consistency is what gives confidence to the computer makers, allowing them to eliminate the need for incoming inspections.
Quality Assurance
Quality assurance is the backbone of customer trust. It involves ensuring products meet certain standards of quality before reaching the customer.
Implementing SPC and using control charts are pivotal parts of a robust quality assurance system. Here's how quality assurance is fortified through SPC:
  • Real-time monitoring of production processes, identifying issues proactively.
  • Reduction of defective products by maintaining process stability.
  • Consistent adherence to quality standards, reducing variation.
By demonstrating process control and stability with control charts, manufacturers reassure customers about the quality of their products.
This trust enables clients, like computer makers, to forego additional inspections after delivery, as confidence in quality is built through reliable processes.
Variation Reduction
Variation is the enemy of consistency in manufacturing. Reducing variation is key to achieving high-quality products consistently.
When variation is minimized, every product is more likely to meet the quality standards. Variation can be reduced by:
  • Identifying and rectifying special causes of variation using control charts.
  • Utilizing SPC tools to maintain process control and prevent defects before they occur.
  • Ensuring all operators follow standardized procedures for reliable results.
By focusing on variation reduction, manufacturers can ensure a higher level of product uniformity.
This directly impacts the quality assurance goals by minimizing the risk of defects. As a result, customer satisfaction increases, and costly inspections can be reduced or eliminated, leading to significant cost savings and increased efficiency.

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Most popular questions from this chapter

When parts are machined, it is important that they are created with enough precision so that they can be assembled with other parts. No machine can hold dimensions exactly, so it is important that there is an agreed upon level of variation. A company that creates nuts and bolts makes their parts with specific tolerances that follow rules established by an international standard. The nut (or hole) has a slightly larger tolerance than the bolt (or shaft) so that the nuts and bolts will work together. This company uses process control, with samples taken five times during each hour, to ensure the processes are stable and running on target. For the nuts, the process is running with \(\mathrm{x}^{-}=10.004 \mathrm{~mm} \overline{\bar{x}}=10.004 \mathrm{~mm}\) and a sigma estimate of all measurements \(s=0.002 \mathrm{~mm}\). For the bolts, \(\mathrm{x}^{-}=10.000 \mathrm{~mm} \overline{\bar{x}}=10.000 \mathrm{~mm}\) with a sigma estimate of all measurements \(s=0.001 \mathrm{~mm}\). Compute the natural tolerances for both the nuts and bolts. What issue do you see with where the process is currently running?

The Department of Transportation reports that about one of every 208 passengers on domestic flights of the 18 largest U.S. airlines files a report of mishandled baggage. Starting with this information, you plan to sample records for 1000 passengers per day at a large airport to monitor the effects of efforts to reduce mishandled baggage. What are the initial center line and control limits for a chart of the daily proportion of mishandled-baggage reports? (You will find that LCL \(<0\). Because proportions \(\mathrm{p}^{\wedge \hat{p}}\) are always zero or positive, take \(\mathrm{LCL}=0 .)\)

A luxury sports car dealership offers its clients a complimentary shuttle service to and from the dealership when they are having their car serviced. Currently, the dealership has a driver to shuttle clients to and from locations. However, using its own driver has drawbacks, because it is a single driver and clients sometimes have to wait an extended period of time in order to get to their destinations. In hopes of improving service and pleasing clients, the dealership decides to change from an in-house shuttle service to using a ride-share service that is still free to the client. The dealership wants to monitor the impact of this change to see if the percentage of clients who take advantage of their transportation service changes. The first thing it does is look at historical data to determine the percentage of clients who have been using the shuttle service. It looked at records for the past 12 months. The average number of clients who visit the dealership each month is 215 , with relatively little month-to-month variation. During the past 12 months, a total of 724 clients have requested rides. (a) What is the estimated total number of clients during these 12 months? What is \(p^{-} \bar{p}\) ? (b) Give the center line and control limits for a \(p\) chart on which to plot the future monthly proportions of clients requesting rides.

A large chain of coffee shops records a number of performance measures. Among them is the time required to complete an order for a cappuccino, measured from the time the order is placed. Suggest some plausible examples of each of the following. (a) Reasons for common cause variation in response time. (b) s-type special causes. (c) \(\mathrm{x}^{-} \bar{x}\)-type special causes.

The unique colors of the cashmere sweaters your firm makes result from heating undyed yarn in a kettle with a dye liquor. The pH (acidity) of the liquor is critical for regulating dye uptake and hence the final color. There are five kettles, all of which receive dye liquor from a common source. Twice each day, the pH of the liquor in each kettle is measured, giving samples of size 5 . The process has been operating in control with \(\mu=5.21\) and \(\sigma=0.147\). (a) Give the center line and control limits for the \(s\) chart. (b) Give the center line and control limits for the \(\mathrm{x}^{-} \bar{x}\) chart.
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