- Anyone with those types of responsibilities understands that keeping equipment running optimally is a careful balancing act.
- Historically, companies have scheduled maintenance and repair based on “averages.”
- Strategic maintenance and repair deliver value in key areas that all have cost-saving implications.
Equipment maintenance and repair data is readily available, or can easily be made available. This can help manufacturers, fleet managers and others in asset-intensive industries maximize uptime — improving both customer satisfaction and profitability.
Digital transformation of the global workplace has impacted every aspect of the way companies do business. Much has been made of how smart, connected technologies are working behind the scenes to ingest, blend, and analyze data 24 hours a day, empowering companies like never before to form closer relationships with their customers and partners, gather market intelligence, and develop targeted products and services.
However, less emphasis has been placed on how companies can use data to introduce new capabilities for optimizing daily operations via data science and analytics. By strategically applying insights from data collected internally, companies can maximize efficiency, proactively manage physical assets, increase staff productivity, improve product and service quality, and enhance logistics.
The Challenge of Equipment Maintenance and Repair
For companies charged with maintaining and repairing equipment, such as the owners of transportation fleets, infrastructure, or production machinery, these new data streams are invaluable.
Anyone with those types of responsibilities understands that keeping equipment running optimally — without investing in unneeded repair or maintenance activities — is a careful balancing act. Under-servicing equipment means risking mechanical or system failure, unexpected downtime, and customer dissatisfaction. But over-servicing is inefficient because it erodes profits and wastes resources.
Fortunately, data that can be collected and shared via the Industrial Internet of Things (IIoT) can provide ongoing feedback on how working equipment is performing over both the short term and long term. Companies that can leverage this data to gain new insights into what is actually happening inside their physical assets have an advantage. They can schedule predictive maintenance, have replacement parts ready at the right time and the right location, and match staff availability and skills with real-world needs.
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Data Is Your Strategic Weapon
Historically, companies have scheduled maintenance and repair based on “averages.” But today it’s no longer good enough to rely on averages to make best guesses. Instead, companies need to leverage actual operating data to optimize these tasks.
Based on data gathered during equipment operation, advanced tools can help companies plan predictive maintenance at the right time — making the most of both human, machine and spare parts assets. Advanced analytics can make strategic repair recommendations based on real-world failure and performance patterns, eliminating last-minute, rushed fixes and minimizing the risk of downtime. Via optimized maintenance scheduling, companies can right-size their spare-parts inventories and allocate parts to the right locations.
While most companies today are still managing maintenance and repair activities by making educated guesses — and tending toward over-servicing their equipment — leading businesses are utilizing data as a powerful strategic weapon. They are using maintenance and repair data to make these tasks more efficient which saves money, improves operations, and enables management to identify opportunities to reallocate resources to other high-value tasks.
The Financial Benefits Are Real
How significant are the financial benefits of data-driven maintenance and repair? A large company operating a fleet of industrial assets implemented advanced technology from Hitachi to provide optimal repair recommendations — supported by data collection, analysis, and artificial intelligence — which enabled technicians to follow a prescribed repair path based on operational knowledge and previous experiences. Using this approach, the company saved 15 minutes on each visit to the repair shop, based on a faster, more accurate diagnosis of equipment failure.
While a 15-minute improvement might seem insignificant, this operator conducts millions of repairs per year across its collection of assets. Based on labor costs alone, this company forecast saving over $15 million annually from this one solution.
In addition to reduced labor costs, strategic maintenance and repair deliver value in these key areas that all have cost-saving implications:
- Increased productivity across all technicians, due to more accurate scheduling and better preparation
- Reduced rework via a higher rate of first-time repair success
- Lower inventory levels and increased geographic accuracy for spare parts
- Increased technician effectiveness due to best-practice adoption
- Improved asset productivity, thanks to a reduction in unplanned downtime
As executives discover the significant return on investment that is possible, more and more businesses are embracing the power of data to fuel intelligent equipment maintenance and repair programs. While some companies are collecting data in new ways by installing smart sensors on their working assets and gathering data in real time, others are simply applying advanced analytics to data they already have — for example, their historic repair and maintenance records — which can lead the way to significant cost savings with relatively modest investments.
Whatever a company’s level of technical sophistication, financial goals, or resource constraints, the breadth of solutions available means that every company can and should begin realizing the benefits of leveraging data to make smarter, more profitable maintenance and repair decisions.
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