17-01-2013, 10:22 AM
Assembly Line Balancing
Assembly Line.ppt (Size: 84.5 KB / Downloads: 53)
Scheduling High-Volume- Low-Variety Operations
The mass consumption patterns of modern industrialized nations depend on assembly line technology.
The classic example is Henry Ford’s auto chassis line.
Before the “moving assembly line” was introduced in 1913, each chassis was assembled by one worker and required 12.5 hours.
Once the new technology was installed, this time was reduced to 93 minutes.
Favorable Conditions
Volume adequate for reasonable equipment utilization.
Reasonably stable product demand.
Product standardization
Part interchange-ability.
Continuous supply of material
Not all of the above must be met in every case.
Concepts
Minimum rational work element
Smallest feasible division of work.
Flow time = time to complete all stations
Cycle time
Maximum time spent at any one workstation.
Largest workstation time.
How often a product is completed.
Inverse of the desired hourly output rate = the amount of time available at each work station to complete all assigned work.
The Problem
Assign tasks to work stations observing balancing restrictions so as to minimize balance delay while keeping station work content for every station cycle time.
Restrictions:
Technological: precedence requirement.
Position restrictions.
Finding a Solution
Heuristic procedures generally allow for a broader problem definition, but do not guarantee optimal solution.
Optimizing procedures generally have used more narrowly defined problems, but guarantee optimal solution.
Examples of optimizing procedures
Dynamic programming
0-1 Integer programming
Branch and bound techniques.
Trend in research has been toward optimizing procedures due to availability of large-scale computers.
Complications
Behavioral options
Job enlargement and rotation.
Wages related to task.
Distribution of slack time.
Inventory buffers.
Involving work group in decisions.
Arranging stations to facilitate interaction.
Personnel selection.
Time to move an item between stations
Machine-dominated work stations.
Task times which exceed the cycle time.
Stochastic task times.
Mixed model assembly lines.