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OPSM 301 Operations Management

Ko ç Un iversity. OPSM 301 Operations Management. Class 13: Service Design Waiting-Line Models. Zeynep Aksin zaksin @ku.edu.tr. Announcements. Lab activity will count as Quiz 2 Exam on 15/11 @ 14:00 in SOS Z27 Study hands-on by solving problems Study class notes

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OPSM 301 Operations Management

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  1. Koç University OPSM 301 Operations Management Class 13: Service Design Waiting-Line Models Zeynep Aksin zaksin@ku.edu.tr

  2. Announcements • Lab activity will count as Quiz 2 • Exam on 15/11 @ 14:00 in SOS Z27 • Study hands-on by solving problems • Study class notes • Read from book to strengthen your background • On 17/11 exam solutions in class • I won’t have office hours on Monday, Canan Uckun will hold additional office hours Monday 13:00-15:00 • Today • Service Design (Ch 7 p. 265-270) • Waiting-Line Models (Quantitative Module D) • Quiz 3

  3. Services .. • .. lead to some desired transformation or improvement in the condition of the consuming unit • …are provided to customers and cannot be produced independently of them • …are produced, distributed and consumed simultaneously

  4. Service Product – Service Process • In most cases the product is your process (eg. concert, amusement park) • Product design involves process design like we have seen before • However customer contact and participation is distinguishing feature • Customer controlled arrivals • Service unique to customer: different service times • Customer experiences process flows

  5. Where is the customer? Service Design Marketing Production Co-production Quality Assurance Measurement

  6. Low High Mass Service Professional Service Personal banking Commercial Banking General purpose law firms Full-service stockbroker Boutiques Retailing High Low Degree of Labor Intensity Service Factory Service Shop Law clinics Limited service stockbroker For-profit hospitals Fine dining restaurants Fast food restaurants Warehouse and catalog stores Hospitals Airlines No frills airlines Degree of Interaction and Customization Customer Interaction and Process Strategy

  7. Service Design Tools: Service Blueprinting • A blueprint is a flowchart of the service process. Answers questions: ‘who does what, to whom?’, ‘how often?’, ‘under what conditions?’ • Shows actions of employee and customer, front office and back office tasks, line of visibility and line of interaction • Instrumental in understanding the process and to improve the design. Are there redundancies, or unnecesssarily long paths? Fail points? Possible poka-yokes that might prevent failures?

  8. Service Blueprint for Service at Ten Minute Lube, Inc.

  9. Separation Self-service Postponement Focus Structure service so customers must go where service is offered Self-service so customers examine, compare and evaluate at their own pace Customizingat delivery Restrictingthe offerings Techniques for Improving Service Productivity Strategy Technique

  10. Modules Automation Scheduling Training Modular selection of service. Modular production Separating services that lend themselves to automation Precise personnel scheduling Clarifying the service options Explaining problems Improving employeeflexibility Techniques for Improving Service Productivity - Continued

  11. If you can’t reduce it, fix it: Contact enhancement • consistent work hours • well trained service personnel • good queue discipline • reduce waiting This motivates our analysis of queueing systems

  12. A Basic Queue Server

  13. A Basic Queue Customer Arrivals Server

  14. A Basic Queue Server

  15. A Basic Queue Customer Departures Server

  16. A Basic Queue Queue (waiting line) Customer Departures Customer Arrivals Server

  17. A Basic Queue Queue (waiting line) Customer Departures Customer Arrivals Server Line too long? Customer reneges (abandons queue) Line too long? Customer balks (never enters queue)

  18. Three Parts of a Queuing System at Dave’s Car-Wash

  19. A common assumption: Poisson distribution • The probability that a customer arrives at any time does not depend on when other customers arrived • The probability that a customer arrives at any time does not depend on the time • Customers arrive one at a time • Interarrival times distributed as a negative exponential distribution

  20. Picture of negative exponential distribution:interarrival times at an outpatient clinic

  21. Independence from other customer’s arrival: interarrival times at an ATM

  22. Time independent arrivals: cumulative arrivals at an ATM

  23. Service system Served units Arrivals Queue Service facility Ship unloading system Ships at sea Empty ships Waiting ship line Dock Single-Channel, Single-Phase System

  24. Service system Served units Arrivals Queue Service facility Service facility McDonald’s drive-through Cars in area Waiting cars Pay Pick-up Single-Channel, Multi-Phase System Cars& food

  25. Service system Served units Service facility Queue Arrivals Service facility Example: Bank customers wait in single line for one of several tellers. Multi-Channel, Single Phase System

  26. Service system Served units Service facility Service facility Queue Arrivals Service facility Service facility Example: At a laundromat, customers use one of several washers, then one of several dryers. Multi-Channel, Multi-Phase System

  27. Arrival Rate ( Queueing Analysis-Performance measures Avg Wait in Queue (Wq) Service Rate ( Avg Number in Queue (Lq)

  28. Processing order Arrivals Waiting Service Exit line System Queueing Analysis Service Rate ( Arrival Rate ( Avg Time in System (Ws) Avg Number in System (Ls) Elements of Queuing System

  29. Waiting Line Models Source Model Layout Population Service Pattern A Single channel Infinite Exponential B Multichannel Infinite Exponential Single channel Infinite Constant C These three models share the following characteristics: Single phase, Poisson Arrivals, FCFS, and Unlimited Queue Length

  30. Notation

  31. Notation

  32. Little’s Law L=  W Operating Characteristics –Model A Utilization (fraction of time server is busy) Average waiting times Average numbers

  33. Example: Model A • Drive-up window at a fast food restaurant: Customers • arrive at the rate of 25 per hour. The employee can • serve one customer every two minutes. Assume • Poisson arrival and exponential service rates. • A) What is the average utilization of the employee? • B) What is the average number of customers in line? • C) What is the average number of customers in the system? • D) What is the average waiting time in line? • E) What is the average waiting time in the system? • What is the probability that exactly two cars will be in • the system?

  34. Example: Model A A) What is the average utilization of the employee?

  35. Example: Model A B) What is the average number of customers in line? C) What is the average number of customers in the system?

  36. Example: Model A D) What is the average waiting time in line? E) What is the average waiting time in the system?

  37. Example: Model A F) What is the probability that exactly two cars will be in the system?

  38. Example: Model B Recall Model A: If an identical window (and an identically trained server) were added, what would the effects be on the average number of cars in the system and the total time customers wait before being served?

  39. Example: Model B Average number of cars in the system (by interpolation)

  40. Example: Model B Total time customers wait before being served

  41. Example: Model C An automated pizza vending machine heats and dispenses a slice of pizza in 4 minutes. Customers arrive at a rate of one every 6 minutes with the arrival rate exhibiting a Poisson distribution. Determine: A) The average number of customers in line. B) The average total waiting time in the system.

  42. Example: Model C A) The average number of customers in line. B) The average total waiting time in the system.

  43. Example: Secretarial Pool • 4 Departments and 4 Departmental secretaries • Request rate for Operations, Accounting, and Finance is 2 requests/hour • Request rate for Marketing is 3 requests/hour • Secretaries can handle 4 requests per hour • Marketing department is complaining about the response time of the secretaries. They demand 30 min. response time • College is considering two options: • Hire a new secretary • Reorganize the secretarial support

  44. 2 requests/hour Accounting 4 requests/hour 2 requests/hour 4 requests/hour Finance 3 requests/hour 4 requests/hour Marketing 2 requests/hour 4 requests/hour Operations Current Situation

  45. Current Situation: waiting times Accounting, Operations, Finance: W = service time + Wq W = 0.25 hrs. + 0.25 hrs = 30 minutes Marketing: W = service time + Wq W = 0.25 hrs. + 0.75 hrs = 60 minutes

  46. Proposal: Secretarial Pool Accounting 2 Finance 2 3 Marketing 9 requests/hour 2 Operations

  47. Proposal: Secretarial Pool Wq = 0.0411 hrs. W= 0.0411 hrs. + 0.25 hrs.= 17 minutes In the proposed system, faculty members in all departments get their requests back in 17 minutes on the average. (Around 50% improvement for Acc, Fin, and Ops and 75% improvement for Marketing)

  48. Cost Total expected cost Minimum total cost Cost of providing service Cost of waiting time Optimal service level High level of service Low level of service Deciding on the Optimum Level of Service

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