Production Planning and Industrial Scheduling Examples, Case Studies and Applications, Second Edition

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