Improving ERP for Mining | Part 1: Planned Maintenance Forecasting - Pronto Solutions Alliance Inc. (PSA)
24-01-2018
Improving ERP for Mining | Part 1: Planned Maintenance Forecasting

As the mining industry matures around the use of Enterprise Resource Planning (ERP) and users become more efficient in operating an integrated solution, it is often difficult to utilize all the functionality a mining-dedicated ERP software solution offers. In researching what mining organizations are doing around the world to manage their operations through intelligent ERP solutions, there are trends available that set best practice operators above the rest. In this series, PSA will explore important business processes that are commonly overlooked in the mining industry.

Any producing mine site should be running an ERP that has an integrated Planned Maintenance module for complete cost visibility, since the maintenance module touches more transactions than any other module, through:

  • Creation and management of work orders
  • Issuing of inventory to work orders
  • Allocation of timesheets to work orders
  • Equipment cost accumulation
  • General ledger integration
  • Rotation of critical spares

Due to high transactional volumes within maintenance, an appropriate forecasting methodology is critical in improving the visibility over costs and operational efficiency. Any ERP system has the ability to use commitments of purchases to track cost-to-complete at project levels or forecast expenditure against budgets. Even though the purchase order commitment functionality is a commonly used and important metric for measuring expected costs, it only accounts for a small portion of transactions. On the other hand, a module generating between 50% – 80% of transactions should garner a more significant focus.

A common reality for a lot of organizations is the lack of readiness or comfort in the information required to forecast accurately. When forecasting planned work over a 1, 3, 6, or 12 month period, it is possible to develop detailed forecasts for:

  • Equipment downtime, leading to accurate availability and utilization estimates
  • Materials requirements
  • Labour scheduling
  • Workshop capacity

There are obvious benefits in being able to predict any of these items with accuracy, and an integrated Planned Maintenance solution makes this possible. If every planned task that is due to be performed on the mobile and fixed plant is logged within the system as a planned task, then any of these items can be successfully forecast.

 

Equipment Downtime

Registering estimated downtime on a planned task allows the production team to plan around equipment delays when scheduling production. Any task that would trigger downtime on a piece of equipment should be tracked. That way, as work is forecast in advance for maintenance, operations can see the equipment’s availability and reduce the impact of maintenance on production. Through registering all expected downtime for each task within a maintenance solution, it is possible to visualize and forecast downtime for the operation.

 

Material Requirements

Inventory replenishment should be automated based upon min/max and commitments within the organization. To assist in the automated process, planned tasks should include material checklists.

This is commonly skipped by mining companies due to the resources it takes for setup, but the benefit is significant enough to warrant the initial effort. Once inventory is linked to planned tasks, the forecast creates internal demand for the inventory against the warehouse, which prompts the procurement team to ensure inventory needs are met for all planned work.

If 60% – 80% of inventory usage transactions are related to maintenance, the significance of material forecasting from an accounting perspective is that the expected cash flow requirements become increasingly apparent. Potential budget discrepancies can then be managed proactively.

The benefit of providing procurement advanced information on their expected replenishment objectives, notwithstanding the benefit from an accounting and finance perspective, is that the largest component of inventory costing becomes manageable and predictable, and rejecting this level of insight into future periods is an oversight that can be easily overcome by allocating resources to the maintenance planning process.

 

Labour Scheduling

Planning maintenance properly allows planners to attach labour types to every task and forecast the labour requirements of maintaining a plant. This is useful primarily because the process allows for the forecasting of labour costs and analyzing labour shortages/overages. Developing a labour schedule makes it possible to visualize where labour is being underutilized and understand how changing the size of a maintenance crew would impact upon budgeted values. In forecasting labour, it is possible to budget a headcount and a maintenance activity based budget and then measure actual hours against this budget to refine the planning process moving forward.

There is significant value in developing an accurate Planned Maintenance plan. As such, the initial efforts required will provide benefit beyond just the planning process. Forecasting costs and managing cash flow are closely related and the accuracy of a maintenance plan have a direct impact on how to manage budgets. Implementing a proper maintenance planning process not only benefits the organization from an operational perspective, but provides relevant information that will help shape the financial analysis process and structure budgets in a meaningful and accurate manner. This is seen as an area of improvement for all mining organizations. The gap between organizations who allocate budget to preparing a detailed maintenance methodology and those that do not is clearly visible.

 

Jarrad Sonnenberg
Manager, Business Development & Advisory

Jarrad is a Pronto Xi ERP software expert with over 10 years of experience in providing ERP implementation and support services to mining, distribution, field service and manufacturing industries.

 

 

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