Big Data for Maintenance Strategies BI103 Why Attend To preserve maintenance data and drive better business decisions, emerging technologies such as Big Data analytics and “Internet of Things” (IoT), where equipment and machinery connect and exchange data through cloud-based CMMS (Computerized Maintenance Management System), can address industrial challenges. Preventative maintenance, predictive maintenance, and life cycle analysis strategies can increase uptimes, whilst reducing operations and maintenance expenditure costs through the use of IoT and Big Data technologies. Participants attending this course will gain an understanding of the nature of maintenance failures and be able to identify equipment classifications and patterns through IoT and Big Data reporting. Participants will have the opportunity to perform cost optimization through effective measurement, reporting and analysis through Big Data, and understand how Artificial Intelligence can be used to predict maintenance requirements, forecasting trends and business requirements. Course Methodology The course is interactive and is comprised of lectures, case studies, technical process learning and supplemental discussions related to various industries and the challenges of implementation. Course Objectives By the end of the course, participants will be able to: Reduce costs through a planned and controlled process utilizing data from cloud based Big Data Ensure a team approach to cost optimization, planning and scheduling throughout the Maintenance and Operations department Create awareness of best practice planning methods and an integrated organizational approach to successful Maintenance Scheduling utilizing cloud based “Internet of Things” IoT and Big Data Improve aligned strategy application throughout the asset, reducing downtime through cloud based IoT and Big Data Develop a clearer understanding of their own and every other team member’s roles and responsibilities within their CMMS system and procedures Target Audience This course is suitable for maintenance Managers, maintenance Planners, Technicians and Supervisors, and all stakeholders in the maintenance support team. Maintenance and reliability Engineers, materials management Managers and Supervisors and all CMMS users would also benefit from this course. Target Competencies Big Data Analytics Maintenance Management IoT Optimization Maintenance Strategy Implementation Cost Optimization Course Outline Maintenance Strategies Assignment using Big Data What is Maintenance and Asset Management using ISO 55000/1/2? IoT and CMMS program management with ISO 27001 and ISO 14224 Maintenance strategies assignment using Cloud based “Internet of Things” IoT and Big Data Predictive Maintenance (PdM) Condition Based Maintenance (CBM) Reliability Centred Maintenance (RCM) through ISO 55000/1 Work Management Process through ISO 9001 Maintenance Program Management utilizing IoT and Big Data information Philosophy of maintenance and how cloud based IoT and Big Data can assist Preventive Maintenance and Predictive Maintenance program function Cost impact and analysis – how cloud based IoT and Big Data can assist reducing costs Maintenance performance evaluation through KPI’s using cloud based IoT and Big Data Proactive maintenance utilizing Big Data, and object code assignments with ISO 27001 and ISO 14224 Implementing Big Data approaches for Maintenance Life Cycle Costing in accordance with Big Data and ISO 14001 Root Cause Failure Analysis (RCFA) in accordance with Big Data and ISO 9001 Objectives of risk management Increasing equipment uptime utilising IoT and Big Data Assignment of organizational roles and responsibilities Developing the inspection sheet Continuous Improvement with Big Data, IoT and ISO standards Using IoT and Big Data for spare parts and material needs Inspection sheet examples Determining the frequency cycle using cloud based IoT and Big Data Effectiveness of Preventive and Predictive Maintenance (PPM) Refining and measuring PPM using cloud based IoT and Big Data Utilizing IoT and Big Data for equipment failure analysis Quality assurance and continuous improvement in accordance with ISO 9000
