An intensive professional development training course on
Big Data Analytics for Predictive Maintenance Strategies
Appropriate Maintenance Strategies
Why Choose Big Data Analytics for Predictive Maintenance Strategies Training Course?
Given the dynamic nature of disturbances and the importance of being lean and agile, it is essential for companies to manage their assets through innovative approaches of maintenance strategy selection and reconfiguration. The Maintenance Strategies and Contracts helps to systematize the decision-making process through response to the current performance of assets and suggest the appropriate decisions to improve performance. Continuous assessment techniques and strategies play a key role in every operation, especially in these unpredictable and highly competitive times. Acquiring strong assessment techniques are essential for every successful leader.
This Big Data Analytics for Predictive Maintenance Strategies training course will improve your abilities to take decisions regarding selection of appropriate maintenance strategies using the concept of the Decision Making Grid (DMG). Delegates will learn to apply assessment techniques with a focus on improvement opportunities using a variety of significant KPIs. Assessment techniques presented will be applied to case studies using group work and general analysis. Delegates are asked to bring information about their organisation, e.g. KPI, current improvement projects, CMMS data, organization mission and goals statements, and any other information they wish to use with the assessment techniques.
This Big Data Analytics for Predictive Maintenance Strategies training course will highlight:
- Classification of maintenance Strategies
- When to use or not to use RCM and TPM
- How to get the most of the CMMS
- Prioritizations and criticality of assets
- Various case studies from different industries and especially oil and gas
What are the Goals?
By the end of this training course, participants will be able to gain a detailed knowledge and skill towards operations and maintenance to enhance the existing skills in assessing the needs, selecting the best resources, managing operations and maintenance of systems and equipment and measure the performance of operations and maintenance providers. More specifically, at the end of this training course, you will learn:
- How to establish and manage outsourcing, contractor performance, monitor regularly and provide management information for continuous improvement
- Define the concept of the DMG, reliability and maintenance strategies "best practice" and be equipped with tools and methodologies to measure and improve organizational performance
- Assess and benchmark the performance of their own organization
- Use readily accessible principles, and studying real-time and historical data, to get a guideline operability
- Develop guidelines for the development of key performance measures specific to the objectives of the organization
Who is this Training Course for?
This Big Data Analytics for Predictive Maintenance Strategies training course is suitable to a wide range of professionals but will greatly benefit:
- Maintenance and Reliability Managers.
- Maintenance and Reliability Supervisors
- Personnel designated as planners, or identified to become planners
- Team leaders from each Maintenance craft
- Key Operations Supervisors
- Materials Management Managers/Supervisors
- CMMS Administrator or key users
- Key Maintenance support assistants
- Other stakeholders in the Work Planning Function
How will this Training Course be Presented?
This Big Data Analytics for Predictive Maintenance Strategies training course will utilise a variety of proven adult learning techniques to ensure maximum understanding, comprehension and retention of the information presented. This includes hands-on, stimulating experience and using interactive user friendly decision analysis software. The training course is highly interactive with many discussion and facilitated practice sessions. Key points will be emphasised with case study examples. There will be a combination of presentation sessions and workshops during in this course.
The Course Content
Day One: Introduction to Maintenance Strategies - The Decision Making Grid (DMG)
- Maintenance decision making and features of Big Data
- Key performance indicators for the DMG
- Utilization of data in the Computerized Maintenance Systems Management (CMMS)
- Methods of partitioning the DMG
- Identification of available maintenance strategies
- Prioritization of responsive decisions
- Application of multiple criteria decision making in the DMG
- Cost-Benefit analysis of the DMG
Day Two: Keep the Best Practice - The OTF Decisions
- Introduction to the concept of best practice ion reliability and maintenance
- Maintenance standards
- Maintenance auditing and benchmarkinG
- Excellence awards in TQM
- Reliability and Maintenance awards
- Application to existing data
Day Three: Investigative Strategies - The CBM Decisions
- Common definitions and terminology
- Standards in Reliability
- Difference between maintenance and reliability
- Reliability modeling approaches and decision making
- Reliability Centered Maintenance (RCM)
- Techniques related to RCM: FMEA, RPN, ICC, FTA, RBD, and MCS
- Condition Base Maintenance technologies
- Application to existing data
Day Four: Human Factors - Skill Levels Upgrade Decisions
- Key performance Indicators (KPIs)
- Overall Equipment Effectiveness (OEE)
- Total productive maintenance (TPM)
- Ask Why 5 times concept
- Learning from others
- Application to existing data
Day Five: Reconfiguration - Design Out Maintenance Decisions
- Getting the best out of data in CMMS
- Integrated framework of the Decision Making Grid (DMG)
- Reconfiguration of the Maintenance and Reliability Structurers
- Guidelines for successful implementation
The Certificate
- AZTech Certificate of Completion for delegates who attend and complete the training course
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