Courses in


GMIT Galway

Postgraduate Diploma in Quality - PART TIME

Open for Applications

Discipline: Science

Location: Galway - Dublin Road

NFQ Level: 9

Programme Duration: Two years

Mode of Study: Part time

Application Route: Apply direct to GMIT

Entry Requirements: Honours Degree (H2.2) in Science, Engineering or Business

Places: 20


See Other Essential Information

CAO Round 1 Points: Not Applicable

Why Study?

If you have been searching for a job you will no doubt have been struck by the number of vacancies with ‘Quality’ in the title or job description. 

This add-on Postgraduate Diploma (60 Credits, Level 9) is designed for people with an honours degree in Business, Science or Engineering who are interested in pursuing a career in quality management or performance improvement and optimisation. 

The purpose of the programme is to fast-track graduates into professional competency levels in key quality areas, identified by the American Society for Quality and The Chartered Quality Institute UK.

Students will have the opportunity to attain high levels of competency in the application of quality management principles for optimising the performance of processes and organisations of all sizes in all sectors of the economy. You will leave the course proficient in areas ranging from Validation through Six-Sigma and Lean. 

You will also be capable of working with others in a regulated environment to maximise the potential benefits of these approaches to any organisation in any sector of the economy.

These areas are:

  • Management systems
  • Interactions of organisations and
  • People and monitoring
  • Control and optimisation

There is significant use of enquiry based learning as part of this programme. 

Programme Modules

  • Management systems and frameworks (5 Credits, Level 9)
  • Validation and Risk Management  (5 Credits, Level 9)
  • Learning and Leadership in Quality  (5 Credits, Level 9)
  • Six Sigma Management  (5 Credits, Level 9)
  • Applied Statistics  (5 Credits, Level 9)
  • Statistical Quality Control  (5 Credits, Level 9)
  • Regulatory and Compliance Management  (5 Credits, Level 9)
  • Leading Transformational Change  (5 Credits, Level 9)
  • System Simulation Modelling  (5 Credits, Level 9)
  • Design of Experiments  (5 Credits, Level 9)
  • Metrology, Verification & Calibration  (5 Credits, Level 9)
  • LEAN value stream optimisation  (5 Credits, Level 9)


Module Aims: 

Programme aims:

  • Provide students with a holistic understanding of the integrated nature of various management systems operating in business
  • Provide students with the knowledge and skills to enable them to work in the area of quality in heavily regulated sectors such as food, medical devices and pharmaceuticals
  • Provide the student with the knowledge and skills to enable them to progress within their workplace, i.e. to up skill or cross-skill within their company
  • Provide students with Level 9 knowledge, skills and competence in line with the National Framework of Qualifications
  • Provide students with the leadership and communications skills required to work at relatively senior levels in the area of quality
  • Support the development of the regulated manufacturing environment in the region

Learning Outcomes: 

Management systems and frameworks

  • Explain the nature of quality from product to societal level.
  • Formulate a methodology to quality improvement appropriate to an organisation's maturity level.
  • Interpret various management standards and frameworks requirements and their relevance to any particular organisation/sector.
  • Develop an integrated approach for organisational compliance to relevant management standards and frameworks.
  • Plan, conduct and evaluate the outcomes of audits at process, system and organisational level

Validation and Risk Management

  • Apply the concepts of risk management to validation projects.
  • Perform simple risk management studies.
  • Analyse the reliability of a process or piece of equipment using FMEA or FTA.
  • Identify when each category of validation is appropriate.
  • Generate a Validation Master Plan, a URS and IQ, OQ and PQ protocols.
  • Interpret the Regulatory requirements in relation to Validation and Risk Management.

Learning and Leadership in Quality

  • Apply a range of professional quality tools and methods in a variety of contexts.
  • Debate the issues and challenges of contemporary approaches to quality.
  • Demonstrate facilitation and leadership skills.
  • Evaluate how reflective practice influences quality.
  • Compose a personal dashboard of competencies

Six Sigma Management

  • Explain the relationship between Lean and Six Sigma.
  • Have an Enterprise wide view of the deployment of Lean Six Sigma
  • Define and Describe Business performance and financial measures of Lean Six Sigma
  • Be able to map out the steps necessary when implementing or helping others implement a Lean Six Sigma program
  • To utilise the Six Sigma Define Measure Analyse Improve Control (DMAIC) toolkit
  • Use Project Management tools such as schedules, Gantt Charts.
  • Apply the seven old and new quality tools and techniques
  • Use strategic and tactical design tools - Porters Five Forces

Applied Statistics

  • Apply probability concepts such as independence, mutually exclusive events, multiplication rules, complementary probability, joint occurrence of events, etc.
  • Apply and interpret the following distributions: normal, Poisson, binomial, hypergeometric, chi square, Student's t and the F distributions.
  • Calculate and interpret the correlation coefficient and its confidence interval, and describe the difference between correlation and causation.
  • Use and interpret the results of hypothesis tests for means, variances and proportions.
  • Calculate and interpret regression analysis, and apply and interpret hypothesis tests for regression statistics. Use the regression model for estimation and prediction.
  • Select, calculate and interpret the results of ANOVAs to determine the importance of a factor and any associated interactions.
  • Define, select and interpret the results of these Goodness-of-fit (chi square) tests.
  • Select, develop and use contingency tables to determine statistical significance.
  • Select, develop and use various non-parametric 

Statistical Quality Control

  • Develop, plot and analyse both variable and attribute Shewhart control charts .
  • Construct and use a EWMA chart.
  • Apply short run and standardised control charts
  • Apply control charts to autocorrelated data.
  • Apply control charts to Multivariate data.
  • Perform process and gauge capability analysis and develop the capability indices.
  • Conduct acceptance sampling by attribute and by variable data using ANSI/ASQC Z1.4 and ANSI/ASQC Z1.9 respectively.

Regulatory and Compliance Management

  • Interpret and apply EU and US Regulatory requirements in a number of product sectors including Medical device and Pharmaceutical product manufacture.
  • Determine the EU Regulatory compliance requirements for CE marking of products.
  • Identify the relevant Conformity assessment procedure for different product groups and demonstrate how these conformity assessment procedures work.
  • Use EU directives to determine Regulatory compliance regime in a number of product sectors.
  • Describe how product liability laws protect consumers in the EU.

Leading Transformational Change

  • Apply a range of advanced professional quality tools and methods in the context of leading transformational change.
  • Assess the role of change agent.
  • Evaluate change methods in work-based scenarios.
  • Compare and contrast leadership styles.
  • Score and justify personal dashboard of competencies.

System Simulation Modelling

  • Apply techniques for developing and validating simulation models
  • Use simulation as a decision support tool.
  • Use an Excel spreadsheet with add-ins, e.g. @Risk, to build simulation models.
  • Use SIMUL8 to build discrete event simulation models
  • Generate random variates for discrete and continuous distributions.
  • Analyse and interpret the results of a simulation model for making a business decision.

Design of Experiments

  • Conduct two and three level fractional factorial experiments and analyse the resulting data.
  • Plan, conduct and analyse experiments using Response Surface Methodology (RSM).
  • Analyse multiple response experiments and interpret the results.
  • Analyse and interpret data from experiments involving random effects models.
  • Use the expected means square rules to develop the appropriate statistical model.
  • Use Minitab to design an experiment, analyse and interpret the resulting data.

Metrology, Verification & Calibration

  • Interpret product and process specifications and specify appropriate measurement and control methodologies.
  • Determine if inspection, test and measurement processes are fit for purpose.
  • Develop measurement management systems appropriate to a company's metrological and regulatory needs.
  • Recognise the importance of process dominance in inspection planning.
  • Identify error proofing possibilities and appropriate approaches.

LEAN value stream optimisation

  • Discuss the lean philosophy.
  • Construct a 'Learning to See' Map
  • Recognise the value stream as a source of competitive advantage.
  • Use value stream mapping tools
  • Develop an improved supply chain
  • Prepare a Lean Value Stream Programme


Management systems and frameworks

  • Quality as an attribute, profession, way of life. 
  • CYSTEM methodology and definitions of excellence. 
  • ISO standards' development process. 
  • ISO9000 quality management system standards.
  • Process Approach, Eight Quality Management Principles, Six core functions. Documentation requirements at system and product/service level. 
  • ISO14000 environmental management systems. 
  • OHSAS 18000 Occupational Health and Safety management system 
  • ISO 22000 Food safety management systems. 
  • IS0 13485 Medical devices quality management systems. 
  • ISO/TS 16949:2009, Quality management systems - Particular requirements for the application of ISO 9001:2008 for automotive production and relevant service part organizations, 
  • ISO19011 Guidelines for quality and/or environmental management systems auditing 
  • Management system Integration. 
  • Frameworks.
  • EFQM Model and definition of excellence.
  • MBNQA Model.
  • Deming Prize. 
  • Self assessment and Benchmarking. 

Validation and Risk Management

  • Risk Management tools commonly used in industry- FMEA, FTA and HACCP, when and how each tool is used. 
  • Sample Risk Management studies- ICH and other Regulatory agencies viewpoint on Risk Management. 
  • ISO 31000:2009 (Risk Management: Principles and Guidelines), Eudralex- Annex 15, ICH Quality Risk Management Q9 guidelines. 
  • Validation categories and when each is relevant. 
  • History of Good Manufacturing Practices and Validation. 
  • Validation documentation and stages- URS, DQ, IQ, OQ and PQ 
  • Overview of equipment and Process Validation studies- Sterilisation, Cleanroom, Cleaning and Software Validation. 
  • Change Control and Revalidation. 

Learning and Leadership in Quality

  •  Learning styles, Problem-based learning and Reflective Practice. 
  •  Reflective practice and personal development; diagnostic and profiling tools: wheel of life, 360degree feedback, transferable skills and competencies. 
  • Personal Dashboard of Competencies: the 'Quality Professional', assessing competencies and evolving a personal dashboard. 
  • Teams: defining teams, team formation, member selection, types of roles, stages of team development, launching teams. 
  • Facilitating teams: team communication, dynamics and motivation. Time management for teams. Creativity and decision-making in teams. Team performance evaluation and reward. 
  • Quality Tools and Methods: Working with ideas: affinity diagrams, tree diagrams, brainstorming, cause and effect/fishbone. Working with Numbers: Check sheet, control charts, histogram, Pareto. Working with Teams: Managing effective meetings, building and maintaining teams.
  • Contemporary Approaches to Quality: TQM, Excellence, Change Models, Systems Thinking, Cybernetics. 8. Leadership: Introduction to leadership theories and styles, leading a team and conflict management. Indicative Practicals and/or Problem Based Learning Scenarios. Design and deliver a training seminar on TQM. Maintain and present an individual reflective practice portfolio and dashboard of competencies.

Six Sigma Management

  • Enterprise-Wide Deployment 
  • Organizational Process Management and Measures 
  • Voice of the Customer 
  • Project Management 
  • Data Collection 
  • Risk Analysis - SWOT 
  • Design for Six Sigma 
  • Strategic and Tactical Design Tools 

Applied Statistics

  • Descriptive Statistics: Measures of Central Tendency and Measures of Dispersion, Sampling. 
  • Laws of Probability: Addition Rule, Multiplication Rule, Conditional Probability, Bayes's Theorem 
  • Discrete Probability Distributions: Binomial, Poisson, Geometric and Hypergeometric distributions. Use of statistical software to calculate probability distributions. 
  • Continuous Probability Distributions: Uniform, Normal and Exponential distributions. Normal distribution as approximation to Binomial. Central Limit Theorem. .
  • Estimation: Point estimation and confidence intervals. Confidence intervals for population mean. T Distribution. Confidence Intervals for a population proportion. Determining sample size. Confidence Intervals for a population variance. Distribution. 
  • Hypothesis Testing: Fundamentals, Testing a claim about a mean, proportion, standard deviation or variance. iii_-values. 
  • Inference from Two Samples: Inference about two means, independent samples and matched pairs. Inference about two proportions. Comparing variation in two samples. F Distribution. 
  • Chi Squared Tests: Goodness of Fit Testing, Contingency Tables 
  • Correlation and Regression: correlation co-efficient, co-efficient of determination, and the standard error of the estimate, prediction intervals, multiple regression. 
  • ANOVA: One way ANOVA, Two way ANOVA 
  • Nonparametric Statistics: Sign test, Wilcoxon test. Use statistical software to perform non parametric tests 

Statistical Quality Control

  • Univariate Control charts: 
  • Introduction to Statistical Process Control (SPC). Review of Common cause and Special cause variation. and R variable control chart. Attribute control charts i.e. p, np, c and u charts. Individual X and Moving Range charts. Average Run Length, Short Run SPC, Standardised Run Charts. Control charts for multiple stream processes. Exponentially Weighted Moving Average (EWMA) charts. SPC for Low Defect Environments. SPC for autocorrelated data. Time series models. Batch means control charts. 
  • The and indices. How to calculate capability indices using the and R method. and indices. Gauge capability studies. Process capability for non-normal data. Introduction to measurement systems analysis. The components of measurement error - Repeatability and Reproducibility (R&R). Precision-to-Tolerance ratio. Determining gauge capability using control charts. Attribute gauge R&R. Tolerance stack-up and interacting dimensions. 
  • Multi-vari plots. Multivariate data and the quality control problem. The chi-squared control chart. The Hotellings T 2 Chart. Interpretation of out-of-control signals. Decomposition. Introduction to principle component analysis. 
  • Principles of Acceptance sampling. Single sampling plans and their associated OC curves. Lot formation considerations. Single, and double sampling plans. The Average Sample Number (ASN). Average Outgoing Quality. 
  • Acceptance Sampling by Attributes (ANSI/ASQC Z1.4). Sampling by Variables (ANSI/ASQC Z1.9) Skip Lot sampling. Continuous Sampling plans. Chain Sampling. 
  • Indicative Practicals and/or Enquiry Based Learning Scenarios. 
  • Assessing the presence of autocorrelation and applying suitable control charts. 
  • Applying transformations to non-normal data and assessing process capability. 
  • Generating multivariate data and observing the deficiencies of univariate control charting techniques. Multivariate control chart techniques will then be applied

Regulatory and Compliance Management

  • Introduction to the EU and US Regulatory authorities and their roles and the specific regulatory requirements. 
  • How organisations meet the EU Eudralex and US CFR requirements in the Pharmaceutical and Medical device sectors. 
  • Product licences and application procedures- National procedure, Mutual Recognition, Centralised and Decentralised procedure. 
  • The roles and responsibilities of the EMA, ICH, PIC-S and GHTF in helping organisations to achieve Regulatory compliance. 
  • CE marking of products- affected products and methods of conformity assessment. 
  • New and Old Approach directives. 
  • Notified bodies and their role, technical files and declarations of conformity. 
  • Introduction to product liability laws in the EU and how these laws can protect the consumer. 

Leading Transformational Change

  •  Change: types of organisational change -missionary, strategic, operational, cultural change. Change methods, organisational development, PDCA, Culture change, best practice examples. 
  • Role of the change agent - definition of role, assessment of skills required. Influence and persuasion in the context of change. 
  •  Leading Change: contingency theories of leadership, transformational leadership, preferred leadership style. 
  • Facilitating Teams: Personal attitudes and resistance to change, negotiation skills and consensus-building. 
  • Advanced Quality tools and methods: Working with ideas: force field analysis, Gantt charts, Interrelationship Digraph, Matrix, Nominal Group Technique. Working with numbers: Process capability, Run, Scatter. 
  • Personal Development Planning: knowledge, skills and competencies of the quality professional. Use of PDP interventions including coaching and mentoring relationships. 
  • Maintaining and developing personal dashboard of competencies in the context of facilitating and leading change

System Simulation Modelling

  • Basic simulation modelling
  • Introduction to Simulation. When is simulation appropriate? When is simulation not appropriate? Advantage and disadvantages of simulation. Areas of application. Components of a system. Discrete event and continuous simulation.
  • Simulation Software
  • Focus on SIMUL8 and @Risk (Excel add-on).
  • Spreadsheet Modelling
  • Developing a spreadsheet model. Concepts. Optimisation modelling. Sensitivity analysis. Simulation of an Inventory system. Lead-time simulation. Supply chain and outsourcing simulation. Warranty model simulation.
  • Simulation Principles
  • Dynamic and stochastic systems. Concepts in discrete event simulation. Developing a discrete event model.
  • Statistical Models in Simulation
  • Review of basic probability and statistical distributions. Simulation of discrete and continuous distributions. Empirical distributions. Models for arrival processes e.g. Poisson process.
  • Queuing Models
  • Characteristics of queuing systems. Queuing notation. Long run measures of performance of queuing systems. Spreadsheet queuing simulation models
  • 7 Random Number Generators
  • Properties. Generation of pseudo-random numbers. Techniques for generating random numbers. Linear congruential method. Combined linear congruential generators. Tests for random number.
  • Generating Random Variates
  • General programming methods for generating random variates. Inverse transform technique. Acceptance-Rejection method.
  • Input Modelling
  • Developing a useful model of input data. Collecting data, Identifying a probability distribution, parameter estimation, Goodness of fit testing. Selecting input models without data.
  • Model Verification and Validation
  • Verification of simulation models. Calibration and validation of models. Face validity. Validation of model assumptions. Input-output validation.
  • Output Analysis
  • Examination of data generated by simulation. Stochastic nature of output data. Output analysis for a single model. Measures of performance and their estimation. Comparing alternative system configurations.

Design of Experiments

  • Stepwise Regression. Multiple Regression. Logistic Regression. Randomised block designs. 
  • Design planning. full factorial Designs. fractional factorial designs. Analysis of Residuals. Blocking in two level designs. Fold-over designs. repeat experiments vs. replicate experiments. Building the regression model and verification of the model. 
  • Analysis of single replicate designs using probability plots. Data transformations in a factorial design, variance stabilisation and Box-Cox transformations. Analysis of multiple response experiments e.g. mean response and variability of response. Overlaid contours. Addition of centre points to a design. Robust methods of experimental design such as Taguchi methods. Solution of static and dynamic problems using Taguchi methods. 
  • Full Factorial Designs, fractional factorial designs, Blocking in and designs, Analysis strategies for multiple responses. 
  • Method of Steepest Ascent, verifying adequacy of first order model. Analysis of second order response surface. Locating the stationary point. Characterising the response surface. Desirability functions. Ridge systems. Multiple response problem. Selecting designs for fitting response surfaces. Central composite designs. Box-Behnken designs. Face centred cube design. Blocking in Response surface designs. 
  • Introduction and Methodology. Simplex Method 
  • The random effects model. Rules for Expected means squares. Repeatability and Reproducibility (R&R) studies using the random effects model. Estimation of variance components. Mixed models. Approximate F tests and Satterthwaite's method. 
  • Crossed vs. Nested designs. Two stage nested design. Diagnostic checking and estimation of variance components. Staggered nested design. The general m-stage nested design. Analysis of Split-plot designs. 

Metrology, Verification & Calibration

  • Management based on facts. 
  • Data types. 
  • The importance of quality data for control, validation, optimisation and decision making.
  • Parameter Tolerances.
  • Metrology the science of measurement.
  • Regulatory bodies.
  • SI units and Standards.
  • Determination of Uncertainty in Measurement.
  • Specifying and selecting appropriate measurement, inspection and test equipment.
  • Measurement System Analysis.
  • Inspection planning.
  • Process dominance.
  • Human errors. 
  • Error-Proofing.
  • Management system standards.
  • ISO9001 Quality management systems - requirements.
  • ISO10012 Measurement management systems - requirements.
  • ISO17025 General requirements for the competence of testing and calibration laboratories
  • Developing and managing internal measurement management systems.
  • Modern inspection, measurement and testing technologies.

LEAN value stream optimisation

  • The Lean Philosophy: Value and Waste. Lean Transformation Frameworks. Strategy, Planning, Deployment. Preparing for Flow. Mapping, Assessment and Analysis. Layout and Cell Design. Scheduling. Improvement. New Product Introduction 
  • Understanding the Value Stream: Value Stream Management. Seven Value Stream Mapping Tools. Applications of Value Stream Mapping. 
  • Strategic Supply Management: Outsourcing. Supply Chain Management. Supply Chain Strategies for Competitive Advantage. Customer-Supplier Relationships. 
  • The Lean Value Stream: The Lean Supply Chain. Lean Information. Accounting and Measurement. Balanced Scorecard. Greening the Supply Chain. Sustainability and Corporate Social Responsibility. 

Essential Information: 


Total fee (Tuition Fee plus Student Contribution) for the full 60 Credit Programme is €6,000, payable as €3,000 in September 2017 and €3,000 in September 2018.  Fees are payable in one instalment per year. Payment by Credit Card, Debit Card, Bank Draft or Postal Order (made payable to GMIT). Payment in cash not possible. A 50% reduction in (Tuition & Student Contribution) fee applies to people in receipt of payments from the Department of Social Protection. Fees are fully refundable up to the day the course starts, thereafter there are no refunds.

Student Cards
Students who enrol for this Programme will qualify for issuing of a GMIT Student ID Card. However if you are undertaking only individual modules within the Programme you will not qualify for issuing of a GMIT Student ID Card.


This is a two year, parl-time course (Fridays 2-10pm)

The course commences the week commencing Monday, 18th September, 2017.

The course is delivered in the GMIT Galway Campus, Dublin Road, Galway. The room will be advised on the Notice Board in Reception.

Closing Date for Applications
Friday, 15th September, 2017. If all places are taken on the course the status of the course will change from “Open for Applications” to “Course Full”.

Application Process

Either complete and return the Application Form or phone the Lifelong Learning Centre on 091 742145 to complete an application form over the phone. 

Contact Us


Course details

Seamus Lennon

Head of Department




Mary Russell

Lifelong Learning Centre,

Northern Entrance, GMIT, Dublin Road

Tel: 091 742 145