Management Science for Decision Support
The emphasis in this module is on formulating (modelling) and solving models with spreadsheets. The topics covered include: modelling principles, optimisation and linear programming, network models, introduction to integer programming, key concepts of probability and uncertainty, decision theory, queuing systems and simulation.
Managing Contemporary Operations: Fundamentals and Challenges
Contemporary operations management is introduced through the vehicle of lectures and case studies. Topics include:
- fundamentals of operations management: operations as a transformation process, the context of operation strategy, how operations add value and enable businesses to compete and/or deliver effective services, differences between services and goods and the goods-service continuum, the role of operations management (strategic, tactical, operational)
- performance measures: developing performance measures for operations and benchmarking (including customer facing)
- types of production (ETO, ATO, MTO, MTS), P:D ratios, role of inventory within operations and supply chain, process design including standardisation, order fulfilment processes and their management
- managing key operations variables: defining capacity and capability, reconciling demand and capacity, handling variety, mass customisation and postponement, service quality vs. cost trade-offs
- 'push' vs. 'pull systems', theory of constraints, JIT, including Toyota production system (TPS)
- detection and elimination of waste and the lean philosophy, practices and techniques
- quality and quality initiatives, unconditional service guarantee
- Step and continuous improvements, issues associated with implementing initiatives and change in general
A factory visit will be organised early on in the module to provide you with some exposure to industrial operations.
Supply Chain Planning and Management
Module content is divided into four parts:
- Supply chain concepts: Classification of supply chains and networks. The importance of supply chain management. The procurement function. Supply chain dynamics. Supply Chain competition.
- Supply chain network design and planning. Buyer-supplier relationships and decisions. Sourcing decisions and lean procurement. Inventory positioning. Coordination and integration. Collaborative forecasting, planning and replenishment. Extended enterprise.
- Logistics management: The relationship between logistics and SCM - scope of the logistics function. Transport and distribution management. Technologies for logistics and SC management. Outsourcing the Logistics function - 3PL and 4PL.
- Supply chain and reverse logistics strategies. Performance, costs, agility and robustness in SCM and Logistics. Strategic planning for integrated SCM and logistics solutions. Sustainable Supply Chains.
Design of Operations Facilities
The module covers: Strategic issues in the location of business in a global environment. Location models and the analysis of factors influencing the optimum selection of country, region and location. The facilities planning process and the optimum design of layouts. Lean manufacturing. Cell manufacturing and just in time production. Material handling and integrated production systems. Warehousing and logistics. Quantitative approaches to location and layout modelling. Computer aided layout design. Planning techniques. Design for next generation manufacturing and services.
Quality Management and Quality Techniques
There are two main divisions of the material:
Historical introduction to the development of quality management thinking. The need for quality, definitions, ideas and concepts of quality. Quality gurus: Deming, Juran, Crosby, Taguchi, etc. Variation and quality improvement, problem-solving tools, Kaizen, Six Sigma. Culture change for Total Quality Management (TQM); empowerment, team-building, motivation. Business excellence awards (MBNQA, EFQM). Quality Management Systems (ISO 9000); auditing and certification. Quality economics, quality performance measures, benchmarking. Supply chain quality. Service quality.
Process capability: Variation Risk Management, loss functions, capability assessment. PCIs, non-normality, Six Sigma approaches. SPC charts: Shewhart charts for attributes and variables. CUSUM, EWMA. Acceptance sampling for attributes and variables. Advanced quality planning - QFD and FMEA. Quality Data management. Taguchi Statistical Robust Design. Total Preventative Maintenance.
Choose three modules from the following list (up to a maximum of two in each semester):
The module covers the following:
- Definitions and classifications of projects
- Objectives in project management - time, costs, quality
- Activity identification
- Resources and resource management
- Critical Path Method, programme evaluation and review technique, and resource scheduling
- Performance measurement and costs
- Project lifecycles and models
- Project teams and leadership in project management
- Managing risk in projects
- Critical Chain Planning Method
- Analysis of project success and failure
- Monte Carlo Simulation
- Project management software
One from the following list:
Advanced Operations Analysis
This module covers the following:
- More advanced forecasting techniques (including more advanced time series and causal models)
- Inventory modelling (quantity discount models; joint replenishment; reorder point , lot size systems; periodic review models; news vendor model; (S-1, S) model; multi-warehouse situations)
- Push/pull/conwip and TOC production systems
- Shop floor control; buffer management and line balancing
- Operations scheduling and sequencing
- Managing variety and variability; Postponement; Mass customisation
- Managing MRP based planning and control systems
- Organising the planning and control function, sales and operations planning and operations planning and control software
Management Science for Decision Support II
In this module, the emphasis is on decision modelling and algorithms for decision making. The topics will include:
- Simplex algorithm for linear programming
- Branch and Bound algorithms for integer programming
- Dynamic programming
- Non-linear programming
- Multi-criteria decision-making
- Combinatorial optimisation and meta heuristics
Examples illustrate the use of these algorithms for decision making.
The module covers the following:
- The simulation approach
- Discrete event simulation
- Computer simulation and software
- Random sampling, experimental design and interpretation of results
- Agent-based simulation
- Web-based simulation
- Continuous system simulation
- Hands-on work with an appropriate simulation software package and associated assessed exercise
Any other module options are subject to approval, pre-requisites and timetabling constraints.
The modules we offer are inspired by the research interests of our staff and as a result may change for reasons of, for example, research developments or legislation changes. This list is an example of typical modules we offer, not a definitive list.