2nd Edition
Production Planning and Industrial Scheduling Examples, Case Studies and Applications, Second Edition
In today's extremely competitive manufacturing market, effective production planning and scheduling processes are critical to streamlining production and increasing profits. Success in these areas means increased efficiency, capacity utilization, and reduced time required to complete jobs. From the initial stages of plant location and capacity determination to plant operations and manpower scheduling, Production Planning and Industrial Scheduling, Second Edition presents a cohesive outlook on optimization and planning. The author provides a focus on practical applications and integrates logistics and planning in the areas of production and scheduling.
Critical Techniques for Optimizing Operational Productivity
Starting with the strategic development of plant locations and capacities, the book lays out a clear process for creating an effective production plan with considerations for existing production facilities. It discusses forecasting and aggregate planning, which can predict demands under scenarios. In addition, the book introduces techniques to improve plant efficiencies in various areas, as well as material requirement and inventory and capacity planning. This expanded second edition features new information on safety stock determination, uncertainty in demand, and resource center capacity planning. The problem-specific case studies illustrate the effect of different procedures on the entire system and stress coordination between independent techniques to help achieve optimal efficiency.
With the aid of this reference and the proper application of its concepts, industrial managers and engineers can reduce their manufacturing cost, succeed in fulfilling their customers' demands in a timely manner, and attain superior planning and overall control of manufacturing operations.
Introduction to Production Planning and Scheduling
Production Planning
Scheduling
What is not included
Plant Locations and Capacity Determination
Existing Production Facilities
New Plant Locations
Uncertainty in Demand
Forecasting and Aggregate Planning
Forecasting
Aggregate Planning
Master Pproduction Scheduling and Material Requirement Planning
Master Production Schedule
Material Requirement Planning and Other Techniques
Inventory and Capacity Planning
Inventory Planning
Safety Stock Determination
Quantity Discounts
Single Period Planning
Consumption during Production
JIT Inventory System
Recourse Center Capacity Planning
Theory of Constraints
A Single Machine Scheduling
The Tardiness Problem
A Survey of Exact Methods for Single Machine Scheduling Problem
Commonly Used Heuristic Rules
Description of an Efficient Heuristic
A Single Machine Problem with Early and Late Penalties
Some Well-Known Theorems
Other Objectives in Single-Machine Scheduling
Common Due Date
Common Due Date Specified by a Customer
Early and Late Due Dates
Quadratic or Nonlinear Penalty Function
Minimization of the Average Delay
Minimization of the Maximum Delay
Minimize the Number of Jobs that are Delayed
Illustrative Example
Maximize the Number of Jobs Processed when the Available Time is Less than Total Processing Time
Sequence-Dependent Jobs
Sequence-Dependent Jobs with Minimum/Maximum
Separations
Minimize Variation of Flow Time
Sequence-Dependent Setup Times
Dual Criteria
Delay of Early Completing Jobs
Jobs Arriving at Different Times
Flowshop Problems
Two-Machine Problem
Three-Machine Problem
Setup/Processing and Removal Times Separated: Another Extension of Johnson's Algorithm
Two-Machine Flowshop with Travel time Between Machines
n Jobs/m-Machines Problem
n-Job/m-Machine Problem: Jobs Arriving at Different Times
Example
Result
Parallel Processing and Batch Sequencing
Parallel Processing
Single Operation Job Related Earliness/Tardiness Penalties With
Machine Activation Cost
Nonidentical Parallel Processors
Parallel Machines in a Flowshop
Batch Scheduling for a Limited-Capacity Fixed-Period Process
Problem
Batch Scheduling for Limited-Capacity Processors, in Sequence with Varying Job Requirements
Batch Sequencing
Network-Based Scheduling
Critical Path Method
To Schedule a Network of Jobs on a Specified Number of Parallel Processors
Scheduling n Jobs on m Parallel Machines when Each Job Can be Scheduled on p Machines, p" Being a Subset of m, that is, p = m
Assembly Line Balancing
Mixed Model Assembly Line Balancing
Mixed-Model Assembly-Method to Minimize Stations
Network Scheduling with Resource Constraint
Job Shop Scheduling
Job Shop
Job Shop Scheduling to Minimize Makespan (SPT)
Network Approach to Job Shop Scheduling
Job Shop Scheduling to Minimize Tardiness
Open-Shop Scheduling
Minimize Makespan: Two-Machine Problem
Minimize Makespan: Multiple-Machine Problem
Minimization of Total Tardiness-Open Shop (MTT-OP)
Minimization of Total Weighted Tardiness Penalties-Open Shop
(MTWT-OP)
Manpower Scheduling
Consecutive Days-off Scheduling
Rotating days (Weekends) off
Monroe's Algorithm
Tour Scheduling
Three Consecutive Days Off
Industrial Sequencing I: Scheduling on NC Machines
Tabular Approach in Group Forming
Job Sequencing to Minimize Tool Changeovers in Flexible
Manufacturing Systems
Heuristic to Minimize Throughput Time on an NC Machine
Problem Definition and Assumptions
Industrial Sequencing II: Electronic Assemblies:
Component
Tape Assemblies on a Sequencer
A Heuristic Procedure for Tape Assembling on a Sequencer
Industrial Sequencing III: Sequencing Feeder for
Component
Tape Assembly
Problem Description
Heuristic Procedure
Industrial Scheduling IV: Scheduling in Flexible Manufacturing
A CDS-Based Two-Phase Algorithm for Group Scheduling with
Multiple Robots in Assembly Operations
APPENDIX: Computer Program Description
INDEX
Each Chapter includes a summary and bibliography
Biography
Dileep R. Sule
"It is a competent text book on these topics, and can be useful for the lecturers and students in industrial engineering and operations management. It also can serve a reference for various relevant models and solution techniques . . . covers practical algorithms of planning and scheduling, the descriptions of each algorithm is formalized at a right level, many numerical examples are provided."
– Vitaly A. Strusevich, in Zentralblatt MATH, 2008
