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Alicia, Nicole & Jason.  Review  The Basics  Terms & Concepts  Statistical Measure  Example  Homework.

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Presentation on theme: "Alicia, Nicole & Jason.  Review  The Basics  Terms & Concepts  Statistical Measure  Example  Homework."— Presentation transcript:

1 Alicia, Nicole & Jason

2  Review  The Basics  Terms & Concepts  Statistical Measure  Example  Homework

3  Total Quality Management: An organization-wide effort directed towards the continuous improvement of quality  Quality as…  “Excellence”  “Conformance to Specifications”  “Fitness for Use”  “Value for the Price”

4  Quality-Related Product Characteristics:  Reliability, Durability, Serviceability  Quality-Related Service Characteristics:  Reliability, Tangibles, Responsiveness, Assurance, Empathy  Design Quality: Inherent value of a product in the marketplace  Conformance Quality: Degree to which the product or service design specifications are met

5  Costs of Quality:  External Failure Costs: Result from defects found after products reach customers  Internal Failure Costs: Result from defects found prior to shipment to customers  Appraisal Costs: Result from inspections to assess quality levels  Prevention Costs: Result from efforts to prevent product defects  Characteristics of OPI Systems:  Vision/mission/purpose for quality  Focus on supplier/customer linkages  Passionate commitment to continuous improvement

6 Product Quality : A product’s fitness for consumption in terms of meeting customers’ needs and desires. Design Quality : A measure of how well a product’s designed features match up to the requirements of a given customer group Conformance Quality : A measure of whether or not a delivered product meets its design specifications Quality Management : A management approach that establishes an organization-wide focus on quality, merging the development of a quality-oriented corporate culture with intensive use of managerial/statistical tools

7 Process-Oriented Focus on Prevention & Problem Solving When managing quality control, management should focus on the process as a whole as opposed to each individual entity Viewing Quality Management as a Never Ending Quest Because products and processes are continually changing, quality management must be continued (even if only small improvements are being made) (Ongoing Process Improvement) Building an Organizational Culture Around Quality Create a culture within the organization that supports quality improvement initiatives

8 Direction of Support Traditional Organizational Structure TQM Organizational View Top Management Middle Management Lower Level Management & Front Line Supervisors Employees Lower Level Management & Front Line Supervisors Middle Management Top Management

9 Act Check Plan Do

10  Definition: A management program that seeks to improve the quality of process outputs by identifying and removing the causes of defects and variation in the various processes  Sigma ( σ ): Represents the standard deviation of values for the output of a process  “Six”: +/- 3 standard deviations

11 1. Define 2. Measure 3. Analyze 4. Improve 5. Control Customers & their priorities Process & its performance Causes of defects Remove causes of defects Maintain quality

12  A set of internationally accepted standards for business quality management systems  Developed by the International Organization for Standardization (ISO) to facilitate international trade  Original: 1987  Newest Version: ISO 9000:2008  Malcolm Baldrige National Quality Award: A national quality award bestowed by the NIST in recognition of superior quality and performance excellence  Given by the US President to strengthen American competitiveness

13  X-bar/R Charts are useful when you want to monitor averages over time but still keep track of the variation between individual results  Note:  X-bar Charts: Subgroup Average ▪ Shows how much variation there is over time in your average  R Charts: Range ▪ Shows how much variation there is within each subgroup  “Statistical Control”: The subgroup average is consistent over time and the variation between a subgroup is consistent over time

14  X-bar –  Subgroup Average  Determines whether a process has shifted to the point that it is no longer “in control”  R –  Range  = Maximum – Minimum  Evaluates the gap between the largest & smallest observations in each sample  Ex. Bowling

15 1. Select subgroup size (n) 2. Select the frequency with which the data will be collected 3. Select the number of subgroups (k) to be collected before control limits are calculated 4. For each subgroup, calculate the subgroup average (Xbar = SX/n) 5. For each subgroup, calculate the group range (R = Xmax – Xmin)

16 1. Select the scales for the x and y axes for both the X & R charts 2. Plot the subgroup ranges on the R chart and connect consecutive points 3. Plot the subgroup averages on the X chart and connect consecutive points

17 1. Calculate the average range (Rbar = SR/k); Plot it on range chart 2. Calculate the overall process average (Xdbar = SXbar/k); Plot it on X-bar chart 3. Calculate control limits for R chart; Plot on R chart 1. (Upper) UCLr = D4Rbar 2. (Lower) LCLr = D3Rbar 3. D3/D4 are control chart constants that depend on group size 4. Calculate control limits for X-bar chart; Plot on X-bar chart 1. (Upper) UCLx = Xdbar + A2(Rbar) 2. (Lower) LCLx = Xdbar – A2Rbar 3. A2 is a control chart constant that depends on subgroup size

18 1. Consider variation 1 st 1. If R chart is out of control, the control limits on the X-bar chart are not valid 2. All tests for statistical control apply to the X-bar chart 1. Points beyond the limits, number of runs & length of runs tests apply to the R chart

19 1. If the R chart is in statistical control, the process standard deviation (s) is: 1. s = Rbar/d2 1.d2 is a control chart constant that depends on subgroup size Control chart constants 

20  A “Run Test”: Checks for patterns in a sequence of observations  Helps an analyst detect abnormalities and provides insight into correcting an out-of- control process  Other indications:  Runs  Hugging  Cycles are similar to Periodocity

21  Example 23: A Quality Control Station  Go through together  Example 24: A Machine with Breakdowns  Homework for Thursday  For “Sheets” buffer, use… ▪ Capacity = 200 ▪ Initial # objects = 200

22  Resources: Resources that this Work Station needs in order to work  To find: Main Menu  Other Features  Resources  Useful in modeling situations where: ▪ 1 person is operating several machines ▪ A machine has several setup configurations ▪ Several other situations  Assigned to Work Stations in the corresponding tables

23  QC @ McDonald’s  http://www.youtube.com/watch?v=kPv2iiJA -ok&feature=related http://www.youtube.com/watch?v=kPv2iiJA -ok&feature=related  Ikea QC Commercial  http://www.youtube.com/watch?v=kP9PZYj VwUo&feature=related http://www.youtube.com/watch?v=kP9PZYj VwUo&feature=related  Toyota QC after recalls  http://www.youtube.com/watch?v=2C- w6ogwr5U http://www.youtube.com/watch?v=2C- w6ogwr5U


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