Service Lifecycle Management (SLM)

Service Lifecycle Management is a flow of tasks for servicing an operating asset. This includes inspections, preventive, predictive and corrective maintenance.

SLM and PLM (Product Lifecycle Management) are interconnected, each feeding the other. The asset operation is based on the PLM outcomes. The collection of data from the operating asset (SLM) is an important input for improving the maintenance and design of future facilities (feeding future PLM).

One of the hot technologies under the SLM umbrella is Predictive Maintenance (PdM). There are many solutions for PdM, where each is used for a specific type of component and industry, therefore, the PdM outputs are also for each individual component.
Asset owners are faced with hundreds of solutions, and may already have thousands of installed sensors, generating billions of data records. At the moment, they do not know what to do with the large amounts of data.

BQR can help you to design a more robust system / product with a more efficient maintenance concept, and furthermore, to integrate all sensors results in real time for asset level maintenance optimization. In addition to predictive maintenance, BQR’s holistic solution also takes into account spare part quantities, spare warehouse locations, repair or replace policy, asset performance, and resources needed to support the maintenance infrastructure.

The starting point of modeling the product / asset is to build a model which reflects the system characteristics: Its availability, reliability of its various components, the maintenance tasks needed to keep the asset running, turnaround-times and cost. The model name is Life Cycle Cost (LCC), and it is the main model that PLM / SLM tool providers should propose to their customers for asset level robustness, data driven decision making, and optimization.

 

List of tools and services BQR offers for Service Lifecycle Management (SLM):

Maintenance & Logistics planning and optimization apmOptimizer	Optimize maintenance and logistics aspects such as: spare parts, inspections, scheduled maintenance, repair or replace.
Statistical analysis of failures and maintenance BQR-Digital	Statistical analysis of failure and maintenance in order to predict approaching equipment failure and plan an effective maintenance strategy.
Field Data Analysis (FRACAS) BQR-Digital	Failure Reporting And Corrective Action System.