BUS606 Study Guide

Unit 7: Facility Analysis – Location and Layout Planning

7a. Describe the criteria for choosing a facility location for manufacturing and service industry firms 

  • What criteria should be considered when choosing a facility location?
  • How might these criteria vary based on the industry?

When choosing a plant location, a cost optimization model is often used by assigning monetary values to the decision attributes. The attributes, or criteria, most often includes market demand, production and storage capacity, production cost, and supply reliability. The cost optimization model can be extended by adding uncertainty into the model – the uncertainty of population, changing market trends, and unpredictability of demand.
 
In the food production industry, additionally, decision attributes must be considered. For example, the assumption of a consistent supply of raw materials, which is possible in most industries, is not possible in the food industry. Deterioration of quality, seasonality of raw materials, unstable climate, and natural disasters must all be part of the determination of location.
 
Even in some industries where raw materials were assumed to be stable, we saw the manufacturing of computer chips disrupted by the worldwide pandemic, leading to production issues for many other industries. Do you think the computer chip manufacturers had a contingency plan developed for such an incident?
 
To review, see Plant Location Selection for Food Production.
 

7b. Compare facility location models, such as the factor rating system, linear programming, and the centroid method, using numerical criteria 

  • How does a locational cost volume profit analysis help us determine a location for a facility?
  • How can we use linear programming to choose the lowest transportation costs between destinations?
  • How has the introduction of Geographic Information Systems affected facility locations?

A locational cost volume profit analysis allows us to determine the best facility location based on forecasted demand over a period of time. By looking at forecasted demand, fixed costs, and variable costs, an analysis can be completed to help decide on a plant location.
 
Linear programming can be used to determine the most effective way to transport products from one location to another with the lowest transportation cost. Products must be transported throughout the supply chain, from wholesalers to distributors, to retailers. Lowering the cost of transportation would increase profits. Because the shipping cost is directly proportional to the number of units shipped, the solution can be determined through linear programming.
 
Geographic Information Systems (GIS) allow us to collect data to store, manage, analyze, and visualize spatial data. While the research study focused on the use of GIS to better understand urban design, land use, and transportation systems, the field of logistics can also benefit from GIS. GIS can help organizations choose restaurant or grocery store locations. GIS can also be used to track inventory during the manufacturing process.
 
To review, see Locational Cost Volume Profit Analysis, Minimizing the Cost of Transportation, and Using Geographic Information Systems.
 

7c. Determine which types of layout are optimal for producing a given product

  • What are the main types of layouts?
  • What industries use each type of layout?

In facility layout, you are trying to determine the best placement for the physical layout of your process. Think about the layout of a manufacturing plant versus a hospital versus a grocery store. All of these organizations have different layout needs. Broadly, we can break the layout planning into two system types: Type 1 is for intermittent processing systems or Process Layout, and Type 2 is for repetitive processing systems or Product Layout. Some organizations use a Hybrid model that combines elements of both Type 1 and Type 2 layouts. Finally, you can have a Fixed-Position Layout, a Type 2 system, where the product is too big to move.
 
To review, see Location, Location, Location: Where Do We Make It? and Introduction to Facility and Product Layout Planning.
 

7d. Evaluate the output efficiency of a given facility layout 

  • What is Assembly Line Balancing, and why is it necessary?
  • How can we classify Assembly Line Balancing?
  • How are these classifications the same? How are they different?
  • What computational models exist to measure output efficiency?

Assembly Line Balancing (ALB) is when an organization uses its resources to meet production rates at a minimum cost. When an assembly line has process changes – such as adding or deleting tasks based on the product produced, a change of components, or a change in processing times, ALB is needed.
 
The problem of ALB can be classified into four categories:

  1. Deterministic Single Model (DSS)
  2. Stochastic Single Model (SSM)
  3. Deterministic Multi/mixed Model (DMM)
  4. Stochastic Multi/mixed Model (SMM)

In the Deterministic models, task times are known, with little variation. The difference between the single and multi/mixed model is the producing a single product versus producing multiple products on one assembly line. In the Stochastic models, task times vary depending on human behavior, complex processes with low reliability, the skill of the workers, and more.
 
Several researchers have developed computational models to measure the efficiency of layouts: Rank and Assign Methods, Tree Search Methods, and Random Sampling Methods.
 
To review, see Mixed Assembly Line Balancing.
 

Unit 7 Vocabulary 

This vocabulary list includes the terms that you will need to know to successfully complete the final exam.

  • Assembly Line Balancing (ALB)
  • Deterministic Multi/mixed Model (DMM)
  • Deterministic Single Model (DSM)
  • facility layout
  • fixed-position layout
  • Geographic Information System (GIS)
  • hybrid model
  • intermittent processing layout
  • linear programming
  • locational cost volume profit analysis
  • process layout
  • product layout
  • rank and assign methods
  • repetitive processing system
  • Stochastic Multi/mixed Model (SMM)
  • Stochastic Single Model (SSM)
  • tree search methods