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Training & Development Techniques
Project Planning Management
This training module will cover the principles of project management and their application in the upstream oil and gas industry. The module also covers the methods and processes of project management, the management of stakeholders, risk management, communication, quality control and project standards as well as the core planning activities that need to be done before the start of a project.
Tools for planning, monitoring, and control of a project. Organising and managing projects. The five main management processes will be demonstrated using a case study to see a project through to completion. These being the; Initiating, Planning, Executing, Monitoring, and controlling & closing.
Energy Audit and Energy Asset Management
This training module covers the topics of energy audit and asset management in industrial processes. The main objectives is to provide participants with an understanding of the basic concepts energy audit and exposure to the relevant international standards before it focuses the strategies and procedures of carrying out energy audit and asset management. Using case studies, the module will examine the techniques for energy audit, managing energy usage, analysis of factors affecting energy efficiency of plant, and cost benefit analysis of introducing alternative strategies and technologies. on completion participants would be able to critically evaluate monitoring tools and assess their usefulness for auditing energy use.
Reliability Centred Maintenance Training
This course will cover changing world of maintenance and its evolutionary perspectives. The RCM seven basic questions and the step-by-step procedure in conducting RCM analysis. The function and failure of complex systems. Failure mode and effect analysis (FMEA). Failure consequences analysis, maintenance and decision making. Failure data analysis and the use of RCM Decision diagram. The nature of failure and technical history and implementing the RCM technique. Use appropriate software to analyse equipment and systems, and support decision making in implementing maintenance strategies will be covered in this module.
Total Productive Maintenance Training
This training course will cover the modern role of care and asset management through TPM and the TPM improvement plan. Planning and launching TPM. Lean maintenance. Maximising equipment effectiveness, and the implementation of autonomous maintenance. Equipment improvement, quality maintenance practices and fault analysis. The use of TPM /concepts (using Fishborne diagram, Overall Equipment Effectiveness (OEE) and 5S).
Predictive Maintenance
Predictive maintenance stems from new opportunities to capitalise on smart digital revolution, and more specifically on advances in decision support tools powered by big data analytics. The wide shift towards smarter industry (Industry 4.0) has revolutionise the maintenance and asset management. On completion of this course participants should be able to: Gain the awareness of the concepts and theory supporting the digital transformation of Asset Care and Asset Support (Operations and Maintenance) using systems engineering approaches and the application of data science in industry. Critically evaluate the KPIs of complex systems and processes using statistical modelling and predictive analytics.
Maintenance Optimisation
This course will cover a variety of formal maintenance optimisation methods used in industry. Types of failures (functional, elementary, observable, hidden), and link with engineering principles. Consequences of functional failure (failure mode, effect and criticality analysis, fault trees, quantitative risk assessment, link with hazard and operability studies and reliability analysis. Cost-benefit analysis of preventive maintenance (age, block, and capital replacement techniques) and inspection techniques. Optimal allocation of manpower (downtime costs, repair cost and spare parts). Scheduling of cost-effective maintenance strategy of systems.
Risk and Criticality Analysis
This module covers the fundamentals of operations and maintenance in the upstream oil and gas industry. It includes topics such as maintenance planning and scheduling, equipment maintenance, and troubleshooting.
CMMS Data Analytics
The use of computerised maintenance management system CMMS and reliable maintenance technique is expected to depend on the use of predictive maintenance and smart data analytics approaches. This will involve harnessing and integrating the relevance of data science, artificial intelligence using stochastic process methodology, statistical analysis, simulation, and expert opinion to predict the lifetime of systems.
Remote Condition Monitoring
The implementation of condition-based maintenance technologies is important to optimise systems/process availability and reliability. The course will cover challenges and the significance of different types of condition monitoring and remote monitoring practices and data information collection from different systems that require adequate maintenance management, planning, and scheduling to ensure high availability and reliability and reduced downtimes.
Statistical Modelling Basics
This course covers the basic descriptive statistics and modelling concept using Monte Carlo and Discrete event simulation approaches.
Forecasting
This course will introduce participant into different forecasting techniques. Time Series analysis such as trend, seasonal, cyclical parametric and irregular component will be covered. The autoregressive (AR), autoregressive and moving average (ARMA), and autoregressive models with integrated moving average (ARIMA) will also be covered in the course.
Digital Twin
The digital twin is based on cumulative, real-world measurements across a wide range of operational parameters. The course will cover the theory the DT concept. The main objectives is to allow participants to become familiar with the components of a DT framework, data, models, algorithms. As part of the module, participants will investigate requirements for DT, domain knowledge, data ontologies, modelling dimensions, architectures, and ML/AI development platforms for instantiation of DT. On completion of the module participants will be able to analyse, transform, and contextualize data from complex systems and processes into information capable of supporting the design, operational and maintenance decisions.
Maintenance Strategy Development
This course will introduce participants into the different type of maintenance strategies. This course provides a framework for managing maintenance, classification of maintenance types and approaches towards the development of maintenance strategies with options that allow decision makers to select the most appropriate cost-effective ways to manage maintenance. The objective of the course is to allow participants to appreciate maintenance and reliability related policies, goals, and strategies and to decide on their uses and limitations. The module will explore the Reliability Centred Maintenance (RCM), Total Productive Maintenance (TPM) and Condition Based Maintenance (CBM) strategies, and on completion the participants will understand how to measure, and compare maintenance practices, and to be able to develop maintenance improvement plan that can deliver the success to a business process.
Reliability Data Analysis
This course will introduce participants into maintenance and reliability terminologies, data collection and analysis. An introduction to descriptive statistical techniques, probability theory and its applications. Exploratory Data Analysis and Basic Statistics such as: Population vs sample, mean, median, mode, standard deviation, skewness, variance, correlation, covariance. Hypothesis testing, statistical distributions, standard error, and confidence interval will be covered.
The effect of redundancy systems and maintenance strategy (including inspection, downtime, man hours and costs) on functional systems reliability will give participants a better insight into the appropriateness of which techniques to use. The course will also examine selected techniques as applied to risk, availability, and maintenance management. In addition, techniques will be treated to analyse field data to report on business targets.
Ethics and Safety Management
This course covers the engineering ethics and health and safety at work act 1974. An introduction into hazard and operability analysis. Accident investigation and management, safety management policies and standards (British Standard adopted by ISO 45001 as BS ISO 45001. The course will also cover contingency planning in the case of major disasters. The aim is to appreciate the relevance of safety to ensure appropriate control measures a put in place.