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Mid-term Review

Mid-term Review. What have we learned so far. Operations Strategy Process Analysis Quality and six-sigma Cases. Operations Strategy. Competitive Dimensions Cost Quality Flexibility Delviery Service What is the role of Operations Strategy in an organization?. Operations Strategy.

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Mid-term Review

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  1. Mid-term Review

  2. What have we learned so far • Operations Strategy • Process Analysis • Quality and six-sigma • Cases

  3. Operations Strategy • Competitive Dimensions • Cost • Quality • Flexibility • Delviery • Service • What is the role of Operations Strategy in an organization?

  4. Operations Strategy • Alignment is key.  In operations decisions, we think about structural decisions and infrastructural decisions • We also want to align with other functional areas (marketing, IT, …), incentives, customer needs, corporate and business unit strategy, organizational culture, suppliers, competitive priorities (cost, quality, flexibility, delivery, service). • Performance measures feed back into the system and inform all of the decisions. • Once you achieve alignment, you can see your competencies and what sets you apart from your competitors.

  5. Process Analysis • Draw Process Flow Diagram • Analyze capacity at each stage • Identify bottleneck  cycle time • Capacity of the system = Time Available/Cycle time • Capacity Utilization = Capacity required/capacity available no start yes end

  6. Process Analysis • The bottleneck task determines cycle time in a sequential process, and cycle time determines capacity. • Managers generally want capacity utilization for any process to be as high as it can be given the performance goals of the process. • Customers use a variety of criteria to evaluate the quality of goods and services – so managers should think about their processes from the customers’ perspective. 

  7. Quality • What is quality • Quality gurus • Quality tools • Six-sigma: • Capability analysis • What is a capable process? • Cp vs. Cpk • Statistical Process Control • X-bar and R chart vs. p chart • What is a in-control process?

  8. Quality • All processes produce output that exhibits variation (Shewhart, Deming, Taguchi). • The costs of prevention and appraisal can be balanced against the costs of internal and external failure (Juaran, COQ framework). • There is a “double whammy” effect from improving yields:  more good units to sell at lower variable cost/unit (relates to Crosby’s notion that “quality is free”). • Quality needs to be managed as a system (Deming). • There is a cost to society of poor quality (Taguchi).

  9. Cost of Quality • Calculate COQ COQ = profit under perfect yield – profit under imperfect yield • Calculate added cost due to imperfect yield at each step

  10. Statistical Process Control • When a process is in control, it exhibits only random variation and reflects the mean and standard deviation of the process found when data were collected on the process. • Statistical “control” is not related to whether a process is producing good output.  Control means that the process is behaving the way we expect it to behave, given what we know about the process. • When a process is capable and in control, when it “does what it does,” it produces output that meets customer specifications. • When monitoring a process with SPC, samples are collected in real-time.  With each sample, one asks the question:  is there any evidence that would lead one to believe that this process has changed?

  11. Statistical Process Control (Cont’d) • Only one SPC chart is required to monitor attributes (occurrences that are counted) because the mean is used to calculate the standard deviation; two SPC charts are required to monitor variables (occurrences that are measured) because the mean and standard deviation are independent. • A process that produces output that is measured can vary in two ways:  the mean can shift (with the variation staying the same) or the variation can change (centered around the same mean). • Sample size for attribute charts (such as percent defective charts) should be large enough to see two of the attribute, on average, in the samples.  For example, if the defect rate is 1%, sample size would need to be 200 to see 2 defects on average. • Frequency of sampling in SPC depends on how stable the process is.  Sampling should be more frequent when a process tends to drift. • Whenever there is SPC evidence that a process is not “behaving the way it is expected to behave, given what is known about the process,” you should look for the assignable cause.

  12. Control Chart Interpretation: Examples UCL = +3 UCL = +3 UCL = +3 UCL = +3 Center Line Center Line Center Line Center Line LCL = -3 LCL = -3 LCL = -3 LCL = -3

  13. X-3sA X-2sA X-1sA X X+1sA X+2s X+3sA X-6sB X X+6sB Upper Specification Limit (USL) Lower Specification Limit (LSL) x Cp P{defect}ppm 1 0.33 0.317 317,000 2 0.67 0.0455 45,500 3 1.00 0.0027 2,700 4 1.33 0.0001 63 5 1.67 0.0000006 0.6 6 2.00 2x10-9 0.00 Process A (with st. dev sA) 3 Process B (with st. dev sB)

  14. Cases we have learned • University Bookstore • Sportswear • Sof-Optics • Manzana • Polaroid

  15. University Bookstore/Sportswear • There are three ways to address an imbalance between capacity and demand:  change time available, change cycle time, shift demand. • Specialized queues: • In and of themselves, don’t improve the performance of a process – unless task times are reduced because of specialization (learning curve).  • May be useful, however, when there is a strategic advantage to the organization. • May affect behavior of customers and therefore improve system performance indirectly. • Whenever we suggest an improvement to a process, we should quantify the effect of the improvement.

  16. Sof-Optics • Solutions should be framed in terms of the organization’s goals and competitive priorities. • Remember there are three ways to address CU problems (not just adding people). • Remember the underlying assumptions when you do calculations – and find a way to adjust for them. • Remember to look at the process when you’re analyzing data!! Managers should be cautious about drawing conclusions from data unless they understand exactly what the data mean. • The behavioral aspects of a process are as important to understand and to manage as the technical aspects. Remember to relate recommendations to employee concerns.

  17. Sof-Optics (cont’d) • When you have a complicated problem, divide it into smaller pieces –  and then conquer! • Don’t forget the cost/benefit analysis.  Build models before you spend and do sensitivity analysis. • Processes should be monitored for key performance measures regularly – not just when problems arise. • You can’t just plan for today – you also have to plan for tomorrow (and at Sof-Optics both demand AND technology are changing). • It’s more difficult to get customers than to keep them (Zero Defections). • Remember the GOAL!

  18. Polaroid • See SPC key points in previous slides for technical elements of the case • Behavioral issues should be considered whenever implementing any improvement effort, including SPC: motivation, leadership, trust. • Whenever there is SPC evidence that a process has changed, you should look for the assignable cause. • Superb operations don’t make up for a strategy that no longer meets customer needs.

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