Operations and Supply Chain Management The Core

228 OPERATIONS AND SUPPLY CHAIN MANAGEMENT
∙ In other processes, the customer is directly involved. For example, when a tooth is removed
at a dentist’s office.
∙ Service systems differ from manufacturing systems in that typically services cannot be
placed in inventory for later use. The process is the product.
∙ The service–system design matrix explores the trade-offs between sales opportunity,
efficiency, and characteristics of the workers in service processes.
∙ Web platform service businesses connect consumers and providers of products and services
through a Web site. They also enable efficient transactions to be processed.
Service package A bundle of goods and services that is provided in some environment.
High and low degree of customer contact A concept that relates to the physical presence of
the customer in the system.
Web platform business A firm that creates value by enabling the exchange of information and
processing of transactions between consumers and providers of a service or product.
LO7–2 Analyze simple service systems.
∙ Service blueprints are a special type of flowchart that places special emphasis on identifying
the high customer contact and low customer contact aspects of a service.
∙ The distinction is made using a “line of visibility” on the flowchart.
Service blueprint A flowchart of a process emphasizing what is visible and what is not visible
to the customer.
Poka-yokes Procedures that prevent mistakes from becoming defects.
∙ Queuing theory is the mathematical analysis of the waiting line.
∙ A waiting line (or queuing) system consists of three major parts: (1) the customers arriving
to the system, (2) the servicing of the customers, and (3) how customers exit the system.
∙ Queuing theory assumes that customers arrive according to a Poisson arrival distribution
and are served according to an exponential service time distribution. These are specific
probability distributions that often match well with actual situations.
∙ There are many different waiting line models; three are studied in this chapter.
∙ Model 1 is useful for simple situations where there is a single line of customers who
arrive according to a Poisson distribution, and who are processed by a single server that
serves each customer in the order they came according to an exponential distribution (for
example, an automated teller machine).
∙ Model 2 is similar to Model 1 with the difference being that it takes exactly the same time
to serve each customer; there is no service variability (for example, a robot making the
same part over and over again).
∙ Model 3 is like Model 1, but two or more servers are available (for example, a bank lobby
with multiple tellers).
LO7–3 Understand waiting line (queuing) analysis.
Queuing system A process where customers wait in line for service.
Arrival rate The expected number of customers that arrive during each period.
Exponential distribution A probability distribution associated with the time between arrivals.
Poisson distribution Probability distribution for the number of arrivals during each time period.
Service rate The number of customers a server can handle during a given time period.
Exponential distribution
Poisson distribution
​f(t) = λ​e −λt [7.1]
n e
−λT ​
​(λT )​
P T (n) = ​ ________ ​ [7.2]
n !