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Job Title


Reliability Consultant


Company : Artificial Intelligence Global Company


Location : Bengaluru, Karnataka


Created : 2025-03-22


Job Type : Full Time


Job Description

Job Title: Reliability Consultant Job Location: Bengaluru (Manyata Tech Park, Hebbal) No. of Positions: 3 This exciting opportunity is responsible for providing reliability engineering, RAM, and Predictive Maintenance (PdM) support for industrial clients. The purpose of this role is to develop robust analysis in determining the reliability of assets, components, equipment, and processes per JLL’s enhanced Reliability & Asset Management program. Core to the role is the validation of asset data either by physical inspection or review of the supplied asset list. The data is then used to continually improve maintenance programs to meet outcome-based performance measures. Responsibilities Works with the client to ensure the reliability and maintainability of new and modified installations. The reliability engineer is responsible for adhering to the life cycle asset management (LCAM) process throughout the entire life cycle of new assets. Participates in the development of design and installation specifications along with commissioning plans. Reliability, Availability, and Maintainability (RAM) modeling and simulation. Participate in the development of criteria for and evaluation of equipment and technical MRO suppliers and technical maintenance service providers. Develops acceptance tests and inspection criteria. Participate in the final check-out of new installations. This includes factory and site acceptance testing to ensure adherence to functional specifications. Guides efforts to ensure reliability and maintainability of equipment, processes, utilities, facilities, controls, and safety/security systems. Professionally and systematically defines, designs, develops, monitors, and refines an asset maintenance plan that includes: Value-added Predictive Maintenance (PdM) tasks Effective utilization of predictive and other non-destructive testing methodologies designed to identify and isolate inherent reliability problems Provides input to a risk management plan that will anticipate reliability-related and non-reliability-related risks that could adversely impact plant operations. Develops engineering solutions to repetitive failures and all other problems that adversely affect plant operations. These problems include capacity, quality, cost, or regulatory compliance issues. To fulfill this responsibility, the reliability engineer applies: Data analysis techniques that can include: Statistical process control Reliability modeling and prediction RAM Fault tree analysis Weibull analysis Six Sigma (6σ) methodology Root cause analysis (RCA) and root cause failure analysis (RCFA) Failure reporting, analysis, and corrective action system (FRACAS ) Works with Production to perform an analysis of assets, including: Asset utilization Overall equipment effectiveness Remaining useful life Other parameters that define operating condition, reliability, and costs of assets Provides technical support to production, maintenance management, and technical personnel. PdM analysis and analytics. Applies value analysis to repair/replace, repair/redesign, and make/buy decisions. Essential Requirements: +10 years of hands-on experience in RAM modeling using Aspentech Fidelis sharing proven portfolio, with at least one of the following certificates (CMRP / CRE / ARPE / CRL). Extensive experience in industrial maintenance, predictive analytics, and data-driven decision-making. Strong background in IoT, machine learning, and statistical modeling for predictive maintenance. Familiarity with maintenance management systems (CMMS, EAM) and ERP systems. Knowledge and certifications of key predictive maintenance technologies (vibration analysis, thermal imaging, ultrasonic testing, etc.). Proven track record of successfully implementing predictive maintenance strategies across various industries. Applies value analysis to repair/replace, repair/redesign, and make/buy decisions. Knowledge of industry standards and regulatory requirements in maintenance practices. Support the integration of predictive maintenance software with existing Enterprise Resource Planning (ERP) and Asset Management Systems (AMS). Qualifications Bachelor’s or master’s degree in (Mechanical/ engineering).