Maintenance

Improving overall operational efficiency through real-time analytical insight into maintenance & asset reliability.

Overview

In the Process Manufacturing Industry, the cost of asset maintenance is approximately 35%- 43% of the total cost of operations (excluding raw material cost). However, maintenance is a critical function in any manufacturing operation to ensure business continuity, reduce unplanned downtime, avoid accidents, etc.

Managing maintenance costs within the planned budget contributes to overall business profitability. It is essential to keep an eye on the critical KPIs and get alerted on non-compliance issues, anomalous trends, clogged workflows, etc.

Customer Profile: Chemical Manufacturing Company

Problem Statement

The customer used various Best-of-Breed applications such as SAP-PM, SAP-MM, and home-grown applications for RBI, Inspection, Corrosion, etc. Despite having multiple IT and OT applications, they faced significant production losses and high maintenance costs.  
Their key issues were :

Solution

The solution lied in extracting value from existing data through analytical insights and foresight of the various performance markers and critical parameters.  

All of the data was analyzed and contextualized by UNLSH to deliver an Operationalized Maintenance & Analytics (Maintenance Digital Twin) solution, which included core KPIs, Analytics Dashboards, and Scheduled Reports.

Impact

The overall performance of maintenance function improved drastically, and the trend was visible in KPI’s such as  

  • Adherence to work-order compliances (e.g., Overdue high priority WO by age)  
  • Extensive reduction in idle capacity and contractor costs
  • Significantly Improved Planning (manpower, shut-downs, spares, certifications, etc.)
  • Major reduction in unplanned maintenance and related costs, etc.  

The impact of UNLSH was not only confined to the maintenance function. Being intrinsically cross-functional, its impact on other operational functions were substantial. For example:

  • Supply Chain – improvements in demurrage, excess/idle inventory, inventory shortage, etc.  
  • Production – drastic reduction in maintenance-related re-planning & re-scheduling, improvement in utilization, etc.

Way Ahead

A solid cross-functional and unified data foundation allowed the customer to target high-impact areas through predictive and prescriptive analytics.  

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