Analysis of a Mixed Model Assembly Line
Essay Preview: Analysis of a Mixed Model Assembly Line
Report this essay
SUMMARY
The following text outlines the design and analysis of a mixed model assembly line and discusses the various effects of different line layouts.
This text will also cover the diferances between two selected work flow processes and discuss the various effects randomness and variation have in a flow process.
INTRODUCTION
The following information demonstrates an understanding of scheduling techniques used in relation to mixed model assembly lines. Using a certain Heuristics Approach, an assembly line will be designed and balanced in a way of achieving maximum productivity. The text will also demonstrate the effects on efficiency when there are changes to product output.
To follow, there will also be discussions concerning the following subjects:
Production lines
Process flow
Randomness in task processing times
Causes of variation in processing times.
DESIGN OF A MIXED MODEL ASSEMBLY LINE
RPWT Heuristics Approach
A heuristic (problem solving technique using readily accessible information) approach can be applied to the mixed model where an assembly line can be produced. In this approach, tasks are prioritised and based on the increasing sum of their processing times. “The sum is called the positional weight of the task, and the tasks with higher positional weights are assigned first. Tasks are assigned to the current open workstation if permitted by their processing time .”
This approach differs from common line balancing techniques due to the fact that this approach operates using a mixed model.
Below is the data provided for this task to produce the mixed model assembly line.
Element
Element Time (Mins)
Preceding Elements
F, G, H
Other data required:
Element B is performed on Y only
Element G is performed on X and Y
Element L is performed on Z only
The three models are to be produced at a rate of:
20 per day for model X
15 per day for model Y
5 per day for model Z
Precedence Diagram for the Product
Using this information, the process can be mapped using a precedence diagram as shown below. This diagram allows the user to visualise the order in which the assembly can be completed using the information above. Using the precedence diagram gives a good indication of which elements are available to be grouped when balancing the workstations.
Fig 1.0
Precedence Diagram
Composite Model
To create the mixed model the information above can be used in a composite model. This model, as shown in the table below, assists with the organisation of the data.
The total number of units/elements column is created by calculating the sum of total number of units for X, Y, and Z per element.
The total time per element is calculated by multiplying the total number of units/elements by the element time.
Element
Element Time
No of Units of Each
Total Number of Units / Elements
Total Time per Element
Positional Weight
Rank (1-12)
Fig 1.1
Incomplete Composite Models
Positional Weight Matrix
Using the previous data a ranked positional weight can be established. The ranked positional weight is a rapid, but approximate, method which has been shown to provide acceptably good solutions quicker than many of the alternative methods. The positional weight is therefore a measure of the size of an element and its position in the sequence of elements. This calculation is basically the sum of the task and all tasks which follow. The general rule is to give the least priority to the task which takes the least amount of time. When arranging workstations, the task with the largest weight should be scheduled first if there is available time within that workstation. The following table is the matrix used to establish each elements positional weight.
Element
Element Time