Maintenance asset data challenges in mining

Three Maintenance Impacts of Asset Data Challenges in Mining

Mining operations are complex, often requiring expensive purpose-built machinery. Maintenance of mining equipment therefore is critical to helping protect capital investments and supporting operational uptime. A critical asset failure can cause operational disruption, which can result in significant losses depending on how long a repair takes. A loss can quickly run up into the $100,000s and higher. With such significant operational impact, it is understandable that maintenance costs in mining are high, especially when more than 60% of the total mine workforce can be almost exclusively focused on servicing or repairing assets in the mine. (source: Miningglobal.com)

The maintenance goal of most mining companies is to make sure their equipment is in good working condition to maximize productivity, minimize downtime and reduce maintenance costs. Ultimately, this means maintenance teams must improve the reliability and availability of physical assets to maximize employee safety, minimize risks, and reduce operating costs. Data is at the center of helping mining companies achieve this goal but current asset data challenges result in: 

• Business decisions based on unreliable or unavailable data. 
• Inefficient utilization of maintenance resources and staff. 
• Difficulty justifying asset replacement and redesign strategies. 

Understanding the asset data-related contributors to each of these challenges provides insight into the capabilities needed to address them. 

Data Reliability and Accessibility Issues

Reliable and accessible data is essential to good business decision-making. Unfortunately, many mining companies struggle with one or more of the issues identified in Table 1. 

Table 1: Key Issues Contributing to Poorly Informed Business Decisions 

The issues cited in Table 1 can make it difficult to get a clear picture of asset health to inform business decisions. A lack of good asset data can cause overly cautious approaches to maintenance that drive operating costs higher without necessarily delivering additional value.  

Inefficient Maintenance Resource Utilization

Without access to trusted asset health data, mining maintenance leaders are often forced to either over maintain equipment or run to failure. Over maintaining equipment to reduce the risk of unplanned failures that cost companies much more in lost production and downtime than the excess maintenance costs. The limited available maintenance staff and equipment that mining companies have, are applied to maintenance tasks that may not actually be the priorities based on pending failure data. Asset health data can deliver valuable insights to help maintenance programs find the right preventative maintenance cadences so that they can shift resources to more imminent maintenance concerns.  

Difficulty justifying asset replacement and redesign strategies

When asset health data is not available or not accompanied by analysis tools, it can be challenging to identify the specific source of failures. Even if data is available, if it is in spreadsheets or distributed across multiple systems, it can be difficult to draw accurate conclusions about failures. The ability to analyze asset health data across the operation and recognize meaningful trends can help maintenance organizations improve long-term maintenance strategies, such as prioritizing asset replacements or redesigning the process or specific equipment. Having available data to support decisions like asset replacement simplifies the financial justification process and makes it easier to get support for maintenance priorities. 

Important Elements for Solving Asset Data Challenges

How do mining companies begin to solve these data challenges and move toward maintenance and operational efficiency improvements? One answer is a unified asset performance management (APM) solution. A singular holistic view of equipment and asset health across a site or even multiple sites can give mining companies the insights needed to optimize maintenance.  

Some key elements of an APM solution that can help mining companies recognize the most value include:  

·                     A fit for purpose solution that delivers mining specific asset health functionality, with predefined models. Quick configuration with minimal engineering effort is essential. 

·                     An asset hierarchy approach to help efficiently track, schedule and identify failure sources. 

·                     A solution that can easily integrate with existing systems, data sources and applications.

·                     A cloud-based approach, which can minimize infrastructure costs, avoids adding to the IT workload, reduce setup time and improve asset health data accessibility. 

·                     Scalability, so that mining companies can add additional assets, analytics, and other features at their own pace. 

Summary

A robust and effective maintenance program is composed of many integrated parts. A single software, system, or tool won’t instantly provide maintenance improvements. However, asset health data is at the heart of delivering operational improvements. Asset Performance Management solutions can be the enabler by providing holistic visibility into mining asset health to help transform equipment data into contextualized asset intelligence. How a mining company interprets and acts on this asset intelligence to inform their business decisions will determine whether they achieve their desired outcomes such as increased revenue, better asset efficiency and decreased operating costs. 

Learn more about our Advanced Mining Solutions: https://www.rockwellautomation.com/en-us/industries/mining-automation.html