MSc Engineering Management for Process Excellence

This module aims to provide students with an in-depth knowledge and understanding of those key concepts, methods, tools and techniques that are fundamental to effective and efficient running of supply chain operations from suppliers’ suppliers to customers’ customers.

The module covers an Introduction to supply chain operations; Demand management; Master planning; Material management; Capacity management; Inventory management; Distribution management; and Case studies.

On completion the participants will be able to design and manage operational supply chain planning, scheduling and controlling systems for complex and disparate operations. In particular, students will:

• Understand the basics of supply chain operations in relation to planning, operating, scheduling and controlling, including knowledge of supply chain operation practices (demand management, master planning, material management, capacity management and inventory management); understanding the impact of supply chain operation practices within commercial and social contexts and global trends in supply chain operation practices
• Identify and assess different methods, tools and techniques for managing plans, operations and materials of end-to-end supply chains
• Demonstrate the ability to apply those methods, tools and techniques in different contexts, including manufacturing and service sectors, with a critical awareness of drivers and obstacles in real life and the ability to produce sensible solutions to overcome them

Assessment and feedback is in the form of 2 in-class tests (60%) and one coursework (40%).

This module aims to provide students with skills and knowledge relating to the use of engineering practices in Project Management with particular respect to the project triple constraint: time, cost and quality.

The module covers: project management principles, concepts and processes; organisational influences, project stakeholders and project lifecycle; project scoping such as project definition, project objectives, project deliverables, and work breakdown structure; Project planning and scheduling: definition of events, activities and nodes, network diagram, analysis of critical path, PERT method and use of industry standard software packages; Project controlling: cost estimate, budget setting, risk identification and assessment and contingency planning.

At the end of this module students will be able to:

• demonstrate a good understanding of project management practices and practical skills to manage project scope – including translating project specifications into work packages
• define and schedule project activities using tools such as critical path and PERT methods; estimate cost and determine budget using analogous and three-point estimating methods; identify and control quality standards using cost of quality and other tools
• develop a good understanding of the inter-dependency between various project management knowledge areas, such as managing projects under constraints; identifying and assessing risks and developing contingency plans
• understand the importance of project stakeholders and their impact on project management, including managing stakeholder relationships

Assessment and feedback is in the form of a group report (50%) and an individual project (50%).

This module aims to develop a critical understanding of operation, structure and implementation issues around enterprise resource planning (ERP) systems as used in industry. Students learn how a typical ERP system works using an up-to-date SAP training package and consider the real-life use of a typical software package within an organisation.

The module covers: Business Excellence; What is ERP?; Business Planning and Control; Expected Benefits; How does ERP work?; ERP Pre-Requisites; Selecting the right system; Implementation Planning.

At the end of this module students will have a critical understanding of:

• terminology relating to MRP, ERPII and ERP
• the benefits and limitations of using ERP systems for making operational, tactical and strategic decisions within businesses, including the ways in which ERP systems may support or hinder decision making at different levels
• learning to operate and build a product in a SAP environment
• the scope, implications, logic, critical requirements to facilitate successful implementation of ERP systems, in particular the relationship between ERP systems, other ICT systems, business processes and human factors

Assessment and feedback is in the form of a 40 minute quiz (40%) and one coursework (60%).

This module aims to provide students with an in-depth understanding of the key principles, concepts, tools and techniques of total quality management and continuous improvement together with an awareness of how these can be used to design and deliver an integrated continuous improvement programme.

It covers an Introduction to Total Quality Management including definitions, basic elements and quality costing; ISO Quality Management System Standards; Quality improvement tools; Reliability Engineering and Continuous Improvement Concepts (FMEA, Lean methodologies, Kaizen, Poka Yoke, Theory of constraints).

At the end of this module students will be able to:

• understand the key principles, concepts, tools and techniques of total quality management and continuous improvement
• apply key principles, concepts, tools and techniques of total quality management and continuous improvement, including planning for real-life application of tools and techniques
• formulate improvement strategies within a particular context

Assessment and feedback is in the form of one group work (a case study report, 40%) and one individual coursework (a journal article, 60%).

This module aims to introduce students to the principles of Lean and Six Sigma. From Continuous Improvement approaches to organisational requirements, the module covers the critical success factors needed to support sustainable and effective business transformation.

The module covers: an Introduction to Lean Thinking, Six Sigma, and Lean Six Sigma (LSS); Comparing and Contrasting Lean & Six Sigma; DMAIC Continuous Improvement Methodology; LSS project characterisation and selection; Lean and Six Sigma metrics; Overview of basic Lean Tools and Techniques including: affinity diagram, project charter, project selection matrices, SPC, Ishikawa, 5 Why’s, 5S, SMED, DoE, etc.; Evolution of Lean Six Sigma (from manufacturing to service environments and the implications of each).

At the end of this module, students will be able to:

• gain an appreciation for Lean Six Sigma as a Continuous Improvement methodology, and understand the implications of its application in manufacturing, transactional and service processes
• apply the Lean Six Sigma methodology (DMAIC) and basic Continuous Improvement tools to solve real world problems
• evaluate the Critical Success Factors and fundamental barriers in the execution of both Lean & Six Sigma initiatives

Assessment and feedback is in the form of an exam (35%) and an assignment in the form of a project report (60%) and project presentation (5%).

This module focuses on innovation implementation. It integrates insights from research and strategy, management control, innovation and technology and organisational behaviour to consider how innovations can be managed. Three main challenges to innovation are explored: resources, organisation and management mechanisms.

The module covers: Management of Innovation including an overview of what makes innovation management complex and three models for how these complexities can be managed; Introduction to Model S for small initiatives; Introduction to Model R for Repeatable Innovations; Introduction to Model C for all other innovations; Build the Team: An Overview and Division of Labour; Assembling the dedicated team and managing the partnership; Creating the Innovation Strategy; Enabling, running and evaluating Disciplined Experimentations.

At the end of this module students will be able to:

• demonstrate a comprehensive understanding of managing the innovation process within organisations
• demonstrate how to integrate business strategy with innovating strategies
• develop the ability to critically assess concepts, tools and techniques of managing innovation for both stable and turbulent environments
• develop and contextualise an approach for analysis for a specific case
• develop an innovation roadmap for strategic purposes

Assessment and feedback is in the form of a group presentation (40%) and an individual final report (60%).

This module aims for students to integrate and apply design, manufacturing and engineering management knowledge and skills to an industry based product and process development project and to develop project management skills.

The module consists of a team-based industrial project where an outline project brief is set by an industrial client. The team is expected to manage all aspects of the project through to a finished solution. This can be a product, system or process depending on the nature of the project. Teams meet with academic staff and industrial clients regularly through the project.

At the end of this module students will be able to:

• have in-depth understanding and knowledge of products and management practices in industry
• critically review and evaluate products and management practices of the particular company and the business impact of proposed solution
• demonstrate knowledge and ability in applying and using various analysis and modelling tools and techniques
• demonstrate project planning and management, presentation, consulting and team working skills
• plan, control and lead an industrial project from inception to completion
• evidence achieving deliverables which meet the client company requirements

Assessment and feedback includes a project report, a presentation to the client and any other deliverables specified in the project brief.

The aim of the individual project is to allow students to combine the skills learned in other modules of the course and apply them within a significant project in a specific area of design, manufacture, or engineering management. This will be achieved through students carrying out work into a particular topic relating to their course and preparing a dissertation that documents the project.

On completion of the module the student is expected to be able to:

• define a valid project in a cutting-edge field of study relevant to the student’s degree – with an appropriate methodology and work plan for the project
• plan, manage and complete project, involving where appropriate technical analysis and independent critical thinking. This involves giving a thorough, logical and critical review of the subject matter; using appropriate tools, processes and levels of analysis in the project and applying project management techniques to manage a successful project
• document their project using suitable presentation techniques (such as language, figures, writing, layout, structure etc.); showing clear evidence of the value of the project and its outcomes and describing the project with clarity

Based on the work of a project, a student will submit an individual dissertation that will account for 90% of the final mark for the class. An interim project justification report will account for the remaining 10% of the mark.

This module aims to introduce students to the theories and principles of Systems Thinking. The module also introduces the methods, tools and techniques for modelling, analysing, improving and designing systems in a variety of organisations including industrial, commercial and public sector.

The module covers: Systems theory, concepts and approaches; Hard and soft systems analysis and systems dynamics; Systems and organisational performance – including leadership in a systems environment and ‘design’ in a systems environment and Practical application of Systems Thinking.

At the end of this module students will be able to:

• show clearer understanding and knowledge of hard and soft approaches and how they can be used to deal with complexity and system behaviour in a business context
• develop understanding of fundamental cybernetic principles that form the foundations of Checkland’s Soft System Methodology and Beer’s Viable System Model
• develop knowledge and skills in systems analysis and business process modelling
• critically evaluate the most appropriate methodology to model, analyse and design engineering/business systems across a range of organisations
• demonstrate an understanding of how to model a business system and to develop a solution to solve a business system problem
• develop an awareness of the importance of system approaches in management interventions

Assessment and feedback is in the form of a group presentation and one coursework in the form of a reflective diary.

This module aims to introduce students to the 'softer' aspects of engineering management. Given some key organisational and technological issues, the main focus is to examine the relationship between “human” elements and change management from an engineering-oriented perspective.

At the end of this module students will be able to:

• discuss key issues in organisation and technology by critically defining and discussing key characteristics of an organisation and evaluating the impact of technology on the workplace of the future
• understand modern people management concepts and practices by evaluating leadership and motivation techniques using analytical approaches and will demonstrate critical understanding of the role of people in a modern organisation
• identify the challenges and consequences of change, including defining and discussing the skills required to handle organisational change and the drivers and obstacles towards organisational change
• understand the impact of organisational and technological issues on people when managing changes. This includes identifying drivers and obstacles from organisational, technological and human perspectives using analytical methods as well as creating strategies to help implement changes

Assessment and feedback is given in the form of:

• group presentations and a group report
• an individual essay

This module aims to introduce the fundamental techniques of risk management, risk-informed decision making and the general principles of risk analysis and its place in risk management, as well as the chance to develop skills in applying these methods to a variety of engineering examples.

The module covers: modelling approaches and methods used by industry currently to manage risk; tools and techniques that are gaining popularity in industry but are not widespread; the basic principles of uncertainty and consequence modelling and the tools and techniques required to apply these principles and Industry standard processes and software tools.

At the end of this module students will be able to:

• understand theory that underpins standard approaches to elicitation of expert judgment
• understand basic theory of fault and event tree modelling
• understand the standard approaches to modelling dependency between random variables
• develop the ability to assess the robustness of a risk model
• understand the standard methods used in ALARP decision-making
• appreciate the consequences of choosing specific measures for risk

Assessment and feedback is in the form of 40% individual work and 60% group work.

This module aims to provide a series of strategic frameworks for managing high-technology businesses. The main focus is on the acquisition of a set of powerful analytical tools which are critical for the development of a technology strategy as an integral part of business strategy. These tools can provide a guiding framework for deciding which technologies to invest in, how to structure those investments and how to anticipate and respond to the behaviour of competitors, suppliers, and customers. The course should be of particular interest to those interested in managing a business for which technology is likely to play a major role, and to those interested in consulting or venture capital.

At the end of this module students will be able to:

• Demonstrate a comprehensive understanding of the role and importance of technology in business strategy formulation process
• Develop the ability to critically assess concepts, tools and techniques of managing technology for both stable and turbulent business environments
• Evaluate complexity and develop appropriate technology strategy models for specific cases

Grades will be determined by class participation assessed through four two-page papers on case studies, which may be written in groups of 4 people (40%), and an individual final technology strategy report based on an in-depth exploration of technology strategy in an assigned industry (60%). There is no final exam.

Quantitative Business Analysis runs over one semester but in two parts. The first part provides an introduction to the basic theory and application of statistical modelling. Topics covered included data analysis, probability theory, distributions and moments, estimation and hypothesis testing.

The second part focuses mainly on two areas - regression modelling and multivariate analysis. While key background theory will be presented, the emphasis is on the generation and interpretation of output from commercially available software.

Background reading for Quantitative Business Analysis

The class is devoted to the concepts and approaches to effective performance measurement and management at an organisational level.

Performance Measurement and Management (PMM) is one of the key factors for survival and prosperity of business systems. Business analysts can typically expect to be involved in the design of PMM systems and in the evaluation of performance information.

This module focuses on the different approaches to performance measurement and management commonly used across public and private sectors. The class focuses at the strategic, and organisational level of PMM while providing the essential knowledge and skills at the technical level.

The module starts with presenting the background of performance measurement to provide the students with an understanding of the roots of some of the common problems in measuring and managing performance in organisations. This will follow with discussing PMM from five different but highly interrelated perspectives, namely stakeholder, customer, comparative, operations and integrative perspectives. Students are encouraged to get more insight into the techniques and concepts by carrying out directed readings as well as completing a group and an individual assignment.

The class will conclude by discussing implementation and managerial issues in measuring business performance.

Every two days, we generate as much data as the data generated in all human history up to 2003,
from online data on every click of the mouse on the internet through the huge upsurge in
manufacturing companies’ use of sensors to sports organisations collecting in-game data. With
these increased quantities of data comes an increased need for tools to make sense of the main
messages coming from these data. This has led to a large upsurge in the area of analytics, both
from the academic community where analytics is now appearing as a keyword in some prominent
journals and the business community with initiatives such as Google Analytics and The Manchester
City Football Club Analytics project.

The class will build on skills and knowledge from the core class MS922: Quantitative Business
Analysis by developing both visualization and advanced analysis techniques relevant in the area
of big data. The focus of the course will be on the application and interpretation of techniques and
there will be an investigation of what makes good data. The class will develop both new theoretical
knowledge in the form of analytics techniques as well as new software skills in relevant analytics
software.

The aim of the class is to help to prepare students to be state-of-the-art business analysts in the
era of big data. It will provide them with the knowledge of and ability to use business analytics tools
in order to make sense of both qualitative and quantitative data, identify the main messages in
those data, and report such messages back to decision-makers appropriately in order to help them
to make better decisions.