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When discussing Predictive Maintenance (PdM), we usually think about the benefits to maintenance engineers and technicians. Much of the discourse is about reducing the number of equipment failures, inspections, and critical infrastructure downtime. Looking beyond the impact on machine health and functionality, there is an added layer of value to the accountants, controllers, and CFOs that manage the finances of an organization, for whom unplanned downtime and accidents can upend any well-planned budget. PdM can help finance departments budget more precisely and allow them to free up cash for alternative purposes.
PdM Enables Just-in-Time Planning for Maintenance
PdM can be compared to Just-in-Time (JIT), the manufacturing and order replenishment process developed in the 1970s. JIT in manufacturing cuts waste by supplying parts only when required by the manufacturing process. This strategy eliminates the need to retain buffer stocks dedicated to each stage in the production process, resulting in massive savings on inventory.
Before the introduction of JIT, inventory was kept for every possible eventuality, just in case a spare was needed. And what happened when the organization overestimated the quantity of spare parts needed? Overspending – much to the dismay of the CFO.
One study found that American companies that introduced JIT saw a 70% average reduction in inventory, a 50% reduction in labor costs, and an 80% reduction in space requirements over the course of only five years.
Today, maintenance in facilities without PdM is similar to the old manufacturing process prior to the introduction of JIT. PdM proves beneficial not only to the maintenance engineers and their ability to keep machines running, but also aids in planning and budgeting of labor, procurement, and inventory.
Any organization that can utilize PdM to prioritize the most important maintenance activities, reduce the human effort required to keep machines working smoothly, and eliminate the need for costly spare parts, can also utilize PdM to accurately predict spending.
The Cost of Unplanned Failures
The absence of a true PdM program inevitably results in unplanned failures and costly consequences. In August of 2016, a single piece of equipment in one of Delta Airlines’ facilities caught on fire, setting off a cascade of failures that led to thousands of flights being canceled or delayed for nearly a week. The consequences go well beyond only lost revenue from those flights. Repairs, replacement parts, work hours, rebooking, re-accommodation and a variety of other expenses, not to mention frustrated customers and loss of brand loyalty, amount to huge costs that could severely impact a company’s budget. At the annual budget review, the fallout of such an incident falls on the finance department.
Among recent stories of natural disasters wreaking devastation across cities and states, there is one example of flooding that could have been avoided. On August 5, 2017 heavy storms led to several inches of rainfall in just a few hours around New Orleans. When those storms hit, six of the city’s most critical pumps were offline for routine maintenance, while some had simply broken down. New Orleans Mayor Mitch Landrieu stated, “We just got really smacked in the wrong place at the wrong time.” The result? Sewage flooding into people’s homes.
Preventive Maintenance is Not Enough
Currently, the vast majority of industries use preventive maintenance programs at their facilities. Such practices, to put it simply, are a big source of budget leaks.
In facilities that adhere to preventive maintenance practices, downtime is planned well in advance, in order to have their equipment inspected and serviced. Mechanical parts are replaced, due to either tangible wear, or based on manufacturer’s’ recommendations. Performance is often tested from start to finish. This means a lot of costly downtime, human resources, and materials. Worse still, performing preventive maintenance does not guarantee machine health – unplanned downtime and unexpected accidents still happen even in meticulously maintained facilities.
Furthermore, we cannot truly budget for major unplanned failures in advance. Because most financial departments do not have access to accurate predictions of equipment malfunctions, they try to over-allocate “just in case” budgeting, ramp up inventory and create multiple redundancies. For most CFOs, it is hard not to wonder whether these wasted funds could have been put to better use elsewhere.
In the age of technologies like the industrial IoT, predictive diagnostics, neural networks and machine learning, preventive maintenance alone is simply not going to cut it. We need to be able to predict when our machines will need maintenance, and therefore become more predictive with our budgeting.
Predictive maintenance helps keep both machines and budgets healthy.
Taking a predictive approach to maintenance brings JIT manufacturing into the maintenance world. Through the use of internet-age systems that provide constant machine monitoring of mechanical data and behavior, organizations are actually able to predict when their machines will require maintenance and what effort and resources will be needed.
Access to such data can prevent unplanned downtime and catastrophic events. Had Delta Airlines received warning that their equipment was at risk of overheating, and had they taken the necessary action to rectify the problem, then a facility fire, a week of canceled flights, stranded travelers and disgruntled customers could all have been avoided.
Predictive maintenance can save companies millions of dollars every year in repair costs alone, not to mention the tremendous reduction in overhead for the financial and planning departments.
There is ample reason why predictive maintenance is beneficial to any company that relies on commercial or industrial assets. For the CFOs, P&L managers and financial planners, PdM impacts the bottom line and can cut waste, minimize surprises, and drive predictive budgeting.
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Author: Issana Raudnitz
Issana is a finance, management and operations expert with over 20 years experience in senior finance, operations and business management roles at both start-ups and established technology companies.