Quantitative Analysis in Operations Management
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This book provides the perfect practice for anybody taking quantitative methods for the first time, or for those looking to brush up on their quantitative knowledge. The books examines the different types of analysis techniques predictive, descriptive, evaluative and optimising through numerous examples and exercises and is great as a stand-alone product or an accompaniment to an Operations Management textbookBackcover Quantitative Analysis in Operations ManagementAlistair Brandon-JonesNigel SlackMaking decisions and bearing the responsibility for them is one of the cornerstones of any ...
This book provides the perfect practice for anybody taking quantitative methods for the first time, or for those looking to brush up on their quantitative knowledge. The books examines the different types of analysis techniques predictive, descriptive, evaluative and optimising through numerous examples and exercises and is great as a stand-alone product or an accompaniment to an Operations Management textbook
Backcover
Quantitative Analysis in Operations Management
Alistair Brandon-Jones
Nigel Slack
Making decisions and bearing the responsibility for them is one of the cornerstones of any operation managers job and its importance is reflected in most texts on the subject. For example, Slack, Chambers and JohnstonsOperations Management provides concepts that support decision making in four major areas: operations strategy, design, planning and control, and improvement. In common with other authors, they explore both qualitative and quantitative approaches, but the lack of space means some aspects of quantitative analysis are not fully explored or are omitted entirely. This is where Quantitative Analysis in Operations Management comes in.
So what do we mean by quantitative analysis? Quantitative analysis involves collecting data that can exist in a range of magnitudes and therefore can be measured in some way. Data then can be organised in such a way as to help decision making. Quantitative Analysis in Operations Management is designed to give you a headstart in the subject and introduce you to the key quantitative methods that are essential to the decision-making process for every operations manager. Packed with examples and exercises this book provides the perfect practice ground for anyone tackling quantitative methods for the first time, or all those looking to brush up their quantitative knowledge!
List of figures
About the authors
Acknowledgements
Using quantitative methods in Operations Management
Models and quantification
Verbal descriptive models
Analogue models
Relationship models
Why use quantitative models?
Types of quantitative model
Predictive techniques
Descriptive techniques
Evaluative techniques
Optimising techniques
1. Predictive Techniques
Introduction
1.1 Time Series Analysis
Simple moving average
Weighted moving average
Simple Exponential smoothing
Trend adjusted exponential smoothing
Seasonality in forecasting
Trend projection
Questions
1.2 Associative Forecasting
Linear regression analysis
Questions
1.3 Forecast Error
MAD, MSE, and MAPE
Questions
2. Descriptive Techniques
Introduction
2.1 Earning Before Interest & Tax (EBIT) and Net Present Value (NPV)
Earnings before interest and tax (EBIT)
Net Present Value (NPV)
Annuity Values
Questions
2.2 Productivity and Efficiency
Productivity
Throughput efficiency
Value-added throughput efficiency
Questions
2.3 Capacity and requirements calculation
Measuring capacity
Design capacity, effective capacity, utilisation, and efficiency
Overall Equipment Effectiveness (OEE)
Calculating requirements single product / service
Calculating requirements multiple products / services
Questions
2.4 Work Measurement
Time studies
Sample size calculation
Work sampling
Questions
2.5 Failure, Reliability and Redundancy
Failure Rate
Mean Time Between Failure (MTBF)
Reliability
Redundancy
Availability
Questions
2.6 Statistical Process Control
Control charts for attributes
Control charts for variables
Process capability
Questions
2.7 Littles Law & Balancing Loss
Littles Law
Balancing loss
Questions
2.8 Queuing methods
M/M/m queuing system
M/M/1 queuing system
G/G/m queuing system
G/G/1 queuing system
Questions
3. Evaluative Techniques
Introduction
3.1 Break-even Analysis
Break-even point for a single product / service
Break-even point for multiple products / services
Evaluating alternative processes
Questions
3.2 Weighted Score Method
Questions
3.3 Decision Theory
Decision-making under certain conditions
Decision-making under uncertain conditions
The value of perfect information
Questions
3.4 Decision Trees
Questions
3.5 Sequencing
Sequencing Rules
Critical ratio
Johnsons Rule sequencing for 2-station flow
Questions
4. Optimising Techniques
Introduction
4.1 Optimising Location
Load-distance method
Load-distance for layout decisions
Centre of gravity method
Questions
4.2 Optimising Inventory
Estimating inventory levels
Economic order quantity
Quantity discounts
Economic batch quantity
The timing decision
Continuous review (Q) system under certain conditions
Continuous review (Q) system under uncertain conditions
Periodic (P) review system
Questions
4.3 Linear Programming
Maximising problems
Minimising problems
The general form of linear programming problems
Questions
4.4 Transportation method
Degeneracy
Supply and demand not equal
Questions
5. Answers
1. Predictive Techniques
1.1 Time Series
1.2 Associative Methods
1.3 Forecast Error
2. Descriptive Techniques
2.1 EBIT & NPV
2.2 Productivity & Efficiency
2.3 Capacity & Requirements Calculation
2.4 Work Measurement
2.5 Failure, Reliability & Redundancy
2.6 Statistical Process Control
2.7 Littles Law & Balancing Loss
2.8 Queuing Methods
3. Evaluative Techniques
3.1 Break Even Analysis
3.2 Weighted Score Method
3.3 Decision Theory
3.4 Decision Trees
3.5 Sequencing
4. Optimising Techniques
4.1 Optimising Location
4.2 Optimising Inventory
4.3 Linear Programming
4.4 Transportation method
6. Formula Review
7. Appendices
Index
Backcover
Quantitative Analysis in Operations Management
Alistair Brandon-Jones
Nigel Slack
Making decisions and bearing the responsibility for them is one of the cornerstones of any operation managers job and its importance is reflected in most texts on the subject. For example, Slack, Chambers and JohnstonsOperations Management provides concepts that support decision making in four major areas: operations strategy, design, planning and control, and improvement. In common with other authors, they explore both qualitative and quantitative approaches, but the lack of space means some aspects of quantitative analysis are not fully explored or are omitted entirely. This is where Quantitative Analysis in Operations Management comes in.
So what do we mean by quantitative analysis? Quantitative analysis involves collecting data that can exist in a range of magnitudes and therefore can be measured in some way. Data then can be organised in such a way as to help decision making. Quantitative Analysis in Operations Management is designed to give you a headstart in the subject and introduce you to the key quantitative methods that are essential to the decision-making process for every operations manager. Packed with examples and exercises this book provides the perfect practice ground for anyone tackling quantitative methods for the first time, or all those looking to brush up their quantitative knowledge!
List of figures
About the authors
Acknowledgements
Using quantitative methods in Operations Management
Models and quantification
Verbal descriptive models
Analogue models
Relationship models
Why use quantitative models?
Types of quantitative model
Predictive techniques
Descriptive techniques
Evaluative techniques
Optimising techniques
1. Predictive Techniques
Introduction
1.1 Time Series Analysis
Simple moving average
Weighted moving average
Simple Exponential smoothing
Trend adjusted exponential smoothing
Seasonality in forecasting
Trend projection
Questions
1.2 Associative Forecasting
Linear regression analysis
Questions
1.3 Forecast Error
MAD, MSE, and MAPE
Questions
2. Descriptive Techniques
Introduction
2.1 Earning Before Interest & Tax (EBIT) and Net Present Value (NPV)
Earnings before interest and tax (EBIT)
Net Present Value (NPV)
Annuity Values
Questions
2.2 Productivity and Efficiency
Productivity
Throughput efficiency
Value-added throughput efficiency
Questions
2.3 Capacity and requirements calculation
Measuring capacity
Design capacity, effective capacity, utilisation, and efficiency
Overall Equipment Effectiveness (OEE)
Calculating requirements single product / service
Calculating requirements multiple products / services
Questions
2.4 Work Measurement
Time studies
Sample size calculation
Work sampling
Questions
2.5 Failure, Reliability and Redundancy
Failure Rate
Mean Time Between Failure (MTBF)
Reliability
Redundancy
Availability
Questions
2.6 Statistical Process Control
Control charts for attributes
Control charts for variables
Process capability
Questions
2.7 Littles Law & Balancing Loss
Littles Law
Balancing loss
Questions
2.8 Queuing methods
M/M/m queuing system
M/M/1 queuing system
G/G/m queuing system
G/G/1 queuing system
Questions
3. Evaluative Techniques
Introduction
3.1 Break-even Analysis
Break-even point for a single product / service
Break-even point for multiple products / services
Evaluating alternative processes
Questions
3.2 Weighted Score Method
Questions
3.3 Decision Theory
Decision-making under certain conditions
Decision-making under uncertain conditions
The value of perfect information
Questions
3.4 Decision Trees
Questions
3.5 Sequencing
Sequencing Rules
Critical ratio
Johnsons Rule sequencing for 2-station flow
Questions
4. Optimising Techniques
Introduction
4.1 Optimising Location
Load-distance method
Load-distance for layout decisions
Centre of gravity method
Questions
4.2 Optimising Inventory
Estimating inventory levels
Economic order quantity
Quantity discounts
Economic batch quantity
The timing decision
Continuous review (Q) system under certain conditions
Continuous review (Q) system under uncertain conditions
Periodic (P) review system
Questions
4.3 Linear Programming
Maximising problems
Minimising problems
The general form of linear programming problems
Questions
4.4 Transportation method
Degeneracy
Supply and demand not equal
Questions
5. Answers
1. Predictive Techniques
1.1 Time Series
1.2 Associative Methods
1.3 Forecast Error
2. Descriptive Techniques
2.1 EBIT & NPV
2.2 Productivity & Efficiency
2.3 Capacity & Requirements Calculation
2.4 Work Measurement
2.5 Failure, Reliability & Redundancy
2.6 Statistical Process Control
2.7 Littles Law & Balancing Loss
2.8 Queuing Methods
3. Evaluative Techniques
3.1 Break Even Analysis
3.2 Weighted Score Method
3.3 Decision Theory
3.4 Decision Trees
3.5 Sequencing
4. Optimising Techniques
4.1 Optimising Location
4.2 Optimising Inventory
4.3 Linear Programming
4.4 Transportation method
6. Formula Review
7. Appendices
Index