COURSE OVERVIEW:

In the era of Industry 4.0, a stand-alone Computerized Maintenance Management System (CMMS) is no longer sufficient. This course focuses on the technical integration of CMMS with Condition Monitoring (CM) and Automated Inspection Systems to create a "Living" maintenance strategy. It centers on the transition from manual data entry to automated, sensor-driven work management, where the machine itself triggers the maintenance request.

The scope of this training involves the architecture of the "Digital Thread," connecting sensors, historians, and predictive analytics to the maintenance work order workflow. Participants will learn how to map diagnostic alerts (vibration, oil, thermography) to specific asset hierarchies and how to configure automated "Condition-Based" work orders. The course explores the challenges of "Big Data" in maintenance, focusing on how to filter high-frequency sensor noise to ensure only actionable intelligence reaches the planning team.

Coverage includes the evaluation of IIoT (Industrial Internet of Things) platforms, the role of API (Application Programming Interface) in data exchange, and the integration of GIS (Geographic Information Systems) for linear assets. Attendees will explore "Smart" inspection protocols where handheld devices sync directly with the CMMS database. By the end of this course, participants will be able to design a fully integrated digital ecosystem that reduces "Wrench Time" on healthy machines and focuses resources on assets showing early signs of degradation.

COURSE OBJECTIVES:

After completion of this course, the participants will be able to:

• Define the architecture of a fully integrated "Condition-Based" CMMS environment.
• Identify the technical requirements for API and middleware data exchange.
• Map condition monitoring "Alert Levels" to CMMS work order priorities.
• Configure automated "Trigger-to-Work-Order" workflows based on sensor data.
• Integrate "Offline" diagnostic data (Oil/Thermography) into the asset record.
• Utilize IIoT sensors to provide real-time usage data for "Meter-Based" PMs.
• Establish data governance rules to prevent "Work Order Flooding" from sensors.
• Integrate digital inspection checklists from mobile devices into the CMMS.
• Utilize "Digital Twins" to visualize asset health across the maintenance team.
• Apply Machine Learning (AI) insights to refine maintenance intervals.
• Measure the ROI of system integration through reduced "No-Fault-Found" work.
• Design a roadmap for transitioning from a "Static" to a "Dynamic" CMMS.

TARGET AUDIENCE:

This course is designed for CMMS Administrators, Reliability Engineers, IT/OT Managers, Condition Monitoring Specialists, Maintenance Digitalization Leads, and Asset Managers.

TRAINING COURSE METHODOLOGY:

A highly interactive combination of lectures, discussion sessions, and case studies will be employed to maximize the transfer of information, knowledge, and experience. The course will be intensive, practical, and highly interactive. The sessions will start by raising the most relevant questions and motivating everybody to find the right answers. The attendants will also be encouraged to raise more of their questions and to share in developing the right answers using their analysis and experience. There will also be some indoor experiential activities to enhance the learning experience. Course material will be provided in PowerPoint, with necessary animations, learning videos, and general discussions.

The course participants shall be evaluated before, during, and at the end of the course.

COURSE CERTIFICATE:

National Consultant Centre for Training LLC (NCC) will issue an Attendance Certificate to all participants completing a minimum of 80% of the total attendance time requirement.