Transcript chapter-13
13–1 Chapter Thirteen McGraw-Hill/Irwin Copyright © 2014 by The McGraw-Hill Companies, Inc. All rights reserved. 13–2 • LO13–02: Analyze process quality using statistics. Copyright © 2014 by McGraw Hill Education (India) Private Limited. All rights reserved. • LO13–01: Illustrate process variation and explain how to measure it. • LO13–03: Analyze the quality of batches of items using statistics. 13–3 • Processes usually exhibit some variation in their output Assignable variation • Variation that is caused by factors that can be identified and managed Common variation Copyright © 2014 by McGraw Hill Education (India) Private Limited. All rights reserved. • The quantitative aspects of quality management • Variation that is inherent in the process itself 13–4 Copyright © 2014 by McGraw Hill Education (India) Private Limited. All rights reserved. • Mean X – the center point of a set of numbers (average) • Standard deviation (σ) – a measure about how much individual observations deviate from the mean (spread). Often referred to as sigma 13–5 Traditional View of Variability Costs Taguchi’s View of Variability Costs Copyright © 2014 by McGraw Hill Education (India) Private Limited. All rights reserved. • Upper specification – the maximum acceptable value for a characteristic • Lower specification – the minimum acceptable value for a characteristic 13–6 Copyright © 2014 by McGraw Hill Education (India) Private Limited. All rights reserved. • The ability of a process to consistently produce a good or deliver a service with a low probability of generating a defect • Specification limits – range of variation that is considered acceptable by the designer or customer • Process limits – range of variation that a process is able to maintain with a high degree of certainty 13–7 Copyright © 2014 by McGraw Hill Education (India) Private Limited. All rights reserved. Process control limits exceed specification limits – process is not capable of meeting requirements 13–8 Copyright © 2014 by McGraw Hill Education (India) Private Limited. All rights reserved. Specification control limits exceed process limits (for improved process) – process is capable of meeting requirements 13–9 • Shows how well the parts being produced fit into the range specified by the design specifications • Cpk larger than one indicates process is capable • When the two numbers are not close, indicates mean has shifted 𝐶𝑝𝑘 = min For the Excel template visit www.mhhe.com/sie-chase14e Copyright © 2014 by McGraw Hill Education (India) Private Limited. All rights reserved. • Ratio of the range of values produced divided by the range of values allowed 𝑋 −𝐿𝑆𝐿 𝐿𝑆𝐿− 𝑋 , 3𝜎 3𝜎 Excel: Process Capability 13–10 Copyright © 2014 by McGraw Hill Education (India) Private Limited. All rights reserved. • The quality assurance manager is assessing the capability of a process that puts pressurized grease in an aerosol can. The design specifications call for an average of 60 pounds per square inch (psi) of pressure in each can with an upper specification limit of 65 psi and a lower specification limit of 55 psi. A sample is taken from production and it is found that the cans average 61 psi with a standard deviation of 2 psi. – What is the capability of the process? – What is the probability of producing a defect? 13–11 13–12 Copyright © 2014 by McGraw Hill Education (India) Private Limited. All rights reserved. Copyright © 2014 by McGraw Hill Education (India) Private Limited. All rights reserved. • Concerned with monitoring quality while the product or service is being produced • Statistical process control - testing a sample of output to determine if the process is producing items within a preselected range • Attributes - quality characteristics that are classified as either conforming or not conforming • Variable - characteristics that are measured using an actual value Excel: Statistical Process Control For the Excel template visit www.mhhe.com/sie-chase14e 13–13 𝑝= 𝑁𝑢𝑚𝑏𝑒𝑟 𝐷𝑒𝑓𝑒𝑐𝑡𝑖𝑣𝑒 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑂𝑏𝑠𝑒𝑟𝑣𝑎𝑡𝑖𝑜𝑛𝑠 Copyright © 2014 by McGraw Hill Education (India) Private Limited. All rights reserved. • Used when an item (or service) is either good or bad (a yes-no decision) 13–14 Calculate the average of the sample proportions. Calculate the standard deviation of the sample proportion. Copyright © 2014 by McGraw Hill Education (India) Private Limited. All rights reserved. Calculate the sample proportions p for each sample. Calculate the control limits. Plot the individual sample proportions, the average of the proportions, and the control limits. 13–15 Copyright © 2014 by McGraw Hill Education (India) Private Limited. All rights reserved. • Used when an item (or service) may have multiple defects 13–16 – Preferable to keep small (usually 4 or 5 units) • Number of samples – Once chart set up, each sample compared to chart – Use about 25 samples to set up chart • Frequency of samples – Trade-off between cost of sampling and benefit of adjusting the system Copyright © 2014 by McGraw Hill Education (India) Private Limited. All rights reserved. • Size of samples • Control limits – Generally use z = 3 13–17 13–18 Copyright © 2014 by McGraw Hill Education (India) Private Limited. All rights reserved. 13–19 Copyright © 2014 by McGraw Hill Education (India) Private Limited. All rights reserved. • Executed through a sampling plan Copyright © 2014 by McGraw Hill Education (India) Private Limited. All rights reserved. • Performed on goods that already exist to determine what percentage of the products conform to specifications • Results include accept, reject, or retest 13–20 • Ensure quality is within predetermined level Copyright © 2014 by McGraw Hill Education (India) Private Limited. All rights reserved. • Determine quality level 13–21 ‒ ‒ ‒ Risks of accepting “bad” lots and rejecting “good” lots Added planning and documentation Sample provides less information than 100 percent inspection • Advantages ‒ ‒ ‒ ‒ ‒ ‒ Economy Less handling damage Fewer inspectors Upgrading of the inspection job Applicability to destructive testing Entire lot rejection (motivation for improvement) Copyright © 2014 by McGraw Hill Education (India) Private Limited. All rights reserved. • Disadvantages 13–22 Acceptable quality level (AQL) Lot tolerance percent defective (LTPD) •Maximum acceptable percentage of defectives defined by producer •Percentage of defectives that defines consumer’s rejection point (producer’s risk) (consumer’s risk) •The probability of rejecting a good lot •The probability of accepting a bad lot Copyright © 2014 by McGraw Hill Education (India) Private Limited. All rights reserved. • Determine (1) how many units, n, to sample from a lot, and (2) the maximum number of defective items, c, that can be found in the sample before the lot is rejected 13–23 13–24 Copyright © 2014 by McGraw Hill Education (India) Private Limited. All rights reserved.