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© DINGO Software Pty. Ltd. 2020 ENTERPRISE PREDICTIVE MAINTENANCE SOFTWARE™
PLAYBOOK
Predictive Maintenance
What’s Inside 1. What is Predictive Maintenance?
2. Play #1: Maximize the Data You Already Have
3. Play #2: Bring All Your Data into One System
4. Play #3: Transform Your Data into Actionable Intelligence
5. Play #4: Implement the Right Process
6. Play #5: Empower Your Employees
7. Customer Success Story
ENTERPRISE PREDICTIVE MAINTENANCE SOFTWARE™© DINGO Software Pty. Ltd. 2020
© DINGO Software Pty. Ltd. 2020 ENTERPRISE PREDICTIVE MAINTENANCE SOFTWARE™
By continuously improving the health and performance of your equipment, Dingo’s solutions increase availability, extend component life, and reduce operating costs.
With predictive maintenance, Dingo customers typically achieve payback in
six months or less and a 3:1 ROI.
What is Predictive Maintenance?
1. “Smart Sensors Help You Predict,” Efficient Plant, November 18, 2018
Many operations use preventive maintenance, the traditional method for keeping equipment maintained and running properly. Preventive maintenance is triggered by factors such as meter readings and manufacturer service recommendations. The downside to this method is that it’s easy to miss something if an equipment issue occurs outside the scheduled maintenance window.
Conversely, predictive maintenance is based on the actual operating condition of your equipment, rather than predetermined factors. A recent study by Accenture and GE found that predictive maintenance can generate a 30% reduction in maintenance costs and as much as a 70% cut in production downtime due to equipment breakdowns.1
DINGO’s asset health software, Trakka®, captures predictive health information from each of your machines and then uses a proprietary analytics platform to assess equipment condition. If problems are found, the system, which seamlessly integrates with your existing workflow, alerts the team and recommends corrective actions.
This early warning system equips maintenance teams with the actionable knowledge required to promptly rectify impending issues, resulting in increased availability and fewer unplanned failures.
© DINGO Software Pty. Ltd. 2020 ENTERPRISE PREDICTIVE MAINTENANCE SOFTWARE™
A common concern when implementing predictive maintenance is data volume. Large mines worry that it’s impossible to collect all their data and derive meaningful insights. Smaller mines, on the other hand, may feel they don’t have enough data to perform predictive maintenance properly. After 25 years in the mining industry, we can assure you that the volume of data is not nearly as important as collecting the right data.
On average, less than 1% of available data in the mining industry is being utilized, which is unfortunate, because it is a critical part of preventing time-consuming and costly equipment breakdowns. Despite the massive amount of data being generated (for instance, a typical new haul truck has over 200 sensors, many generating multiple readings per second), mines still experience unplanned breakdowns and shorter than expected equipment lives.
Another issue is that common preventative management data, such as oil sample results, often isn't being utilized properly, because it's analyzed in isolation from other condition data. How much more valuable would those results be if they were examined in conjunction with sensor or vibration data?
Dingo's award-winning software, Trakka, brings all your condition monitoring data sources together into one centralized system. By providing the complete picture, maintenance teams can pinpoint the corrective work required to keep assets healthy and drive tangible cost and productivity savings.2. The Healthy Digital Mine, Dingo.
On average, less than 1% of available data in the
mining industry is being used 2
Play #1: Maximize the Data You Already Have
Dingo partners with your operation to capture and analyze data, manage workflows, and
maximize equipment performance.
Your Operations Our Process
Listening to Asset
Analyzing with human expertise & proven technology
Creating actionable intelligence
Maximizing Asset Health
Collecting Data
Onboard Sensors
Machine Operating Data
���� Condition Data
ERP Work History
Inspection with Mobile App
© DINGO Software Pty. Ltd. 2020 ENTERPRISE PREDICTIVE MAINTENANCE SOFTWARE™
It’s not uncommon for mines to have data siloes, where their condition monitoring data is generated by different systems and reviewed by different people. However, fragmented systems and data storage make it easy to miss critical pieces of the puzzle, which can result in issues snowballing into larger and more expensive problems.
The solution is to bring all your data together into a centralized predictive maintenance system, like Dingo Trakka, which fits seamlessly within yourooperations. Employees, even those in different departments, will have access to
the same information so they can make well-informed decisions.
It can seem daunting to bring together all your data, but Dingo makes it easy with its vast Data Connector library, a comprehensive set of data connections that are preconfigured to seamlessly connect and interface with condition monitoring data providers, ERP systems, and mobile field inspection devices.
The result is that the bulk of the heavy lifting is done for you, which means siloed data can rapidly be transformed into actionable intelligence.
Play #2: Bring All Your Data into One System
Trakka captures the majority of your condition monitoring data including:• Comprehensive condition data spanning OEMs and equipment all in one system.
• Seamless integration to labs and data providers via existing connections.
• Direct integration with your ERP system so corrective maintenance work flowsdirectly into work orders.
You’ll no longer need to bounce back and forth between spreadsheets that track vibration, oil, and inspection data to determine if potential issues are brewing, because it can be analyzed in a single pane of glass so issues are easily identified and rectified.
© DINGO Software Pty. Ltd. 2020 ENTERPRISE PREDICTIVE MAINTENANCE SOFTWARE™
Play #3: Transform Your Data into Actionable Intelligence
A key point Dingo has learned from over 25 years in the mining industry is that collecting volumes of data without a clear goal for its intended use adds complexity and delivers little value. It’s critical to apply context to your data to transform it into meaningful actions that make a material impact on your mine’s performance and productivity.
It’s important to use data as a means to an end by starting with your goals and working backwards to determine what data and analysis is required to achieve them. Ultimately, you want to answer the question: “What are we going to do with this information?”
For example, let’s say two streams of sensor data on a haul truck point to an emerging problem. In isolation, that data isn’t very actionable, because other factors also need to be taken into account including: What is the impact on production if the truck is taken out of service? When was its last maintenance performed? Is this a one-off or recurring problem?
To answer these questions, the bigger picture needs to be examined. Trakka uniquely
blends predictive analytics with human expertise to apply context to your condition monitoring data. This holistic platform then helps your team connect the dots between data, actions, and events to generate predictive insights and recommend actions that prevent costly issues before they arise.
Our team of Condition Intelligence experts add further context that can only come from the well-trained, human eye. These experts manage the condition of over 170,000 vital components every day for operations worldwide.
Considering many mines, especially those with remote operations, are finding it difficult to hire employees with mining expertise, Dingo’s Condition Intelligence experts can supplement your workforce by providing daily reviews of all your condition monitoring data. With over 800 years of combined maintenance experience they can help your operation quickly and cost-effectively implement a world-class predictive maintenance program.
© DINGO Software Pty. Ltd. 2020 ENTERPRISE PREDICTIVE MAINTENANCE SOFTWARE™
ONE SYSTEM TO PREDICT AND PERFORM
+ All data managed in one system+ Seamless integration to data providers
+ Holistic view of Asset Health+ Proven algorithms optimized over
25+ years
+ Direct integration with ERP+ Issues are tracked until equipment
returns to normal
+ Knowledge and confidence to extend component life + Value is captured in system after
issues are resolved
Play #4: Implement the Right Process
COLLECT
ASSESS
ACT
RESOLVE
CO
NTI
NU
OS
FEED
BAC
K LO
OP
HEALTHY ASSETS = IMPROVED AVAILABILITY & EXTENDED LIFE
UNITING PREDICTIVE ANALYTICS WITH WORKFLOW MANAGEMENTto empower your maintenance team to make the right decisions at the right timeUNITING PREDICTIVE ANALYTICS WITH WORKFLOW MANAGEMENT to empower your maintenance team to make the right decisions at the right time
HEALTHY ASSETS = IMPROVED AVAILABILITY & EXTENDED LIFE
Many mines assume that they need to throw out their existing processes in order to implement predictive maintenance. With Dingo, that’s not the case – Trakka will support your existing maintenance processes so you won’t need to make significant changes to what you’re already doing. For example, if you’re using an ERP system, Trakka can be a powerful complement by directly integrating with it or operating in parallel.
Many mines use a traditional ‘checkbox’ approach of closing out an issue when a work order is complete. However, this focus on task completion often doesn’t resolve the root cause of the problem.
Trakka combines predictive analytics with workflow management, including closed loop, continuous monitoring and action tracking. Issues stay open and are closely tracked until your equipment returns to its normal operating state. This approach increases asset availability and optimizes resource utilization.
© DINGO Software Pty. Ltd. 2020 ENTERPRISE PREDICTIVE MAINTENANCE SOFTWARE™
Play #5: Empower Your Employees
It can be challenging to change the status quo, but we’ve done it successfully many times for mines around the world. To help you smoothly transition to predictive maintenance, dedicated Dingo experts are with you each step of the way and run a variety of implementation and training sessions to guide your employees through the transition. The goal is to help your people do their best work and give them the tools and processes they need to be successful.
In order to gauge the ongoing performance of your predictive maintenance program and improve compliance, it’s important to measure results that tie directly to your KPIs. Using Asset Health and Performance dashboards, Trakka shows condition data from the operation down to the component level, so you can quickly and easily track performance, drill down to the desired level of detail, and alert team members to potential issues.
You can also measure the financial impact of each maintenance decision using Trakka’s financial tracking system. You’ll have access to quantifiable data on breakdown avoidance savings, including parts and downtime, along with component life extension savings. Employees can login and immediately understand their impact by viewing how equipment health has improved over time and the financial significance of each save.
To help your team manage Asset Health on the go, they can easily access, understand, and act on equipment’s condition – anytime, anywhere − with Dingo’s Trakka Asset Health ManagerTM App. Equipment operators can view equipment health, recommend a course of action and then track its progress through issue resolution, all from their mobile device.
Employees can view current fleet health and issues on their mobile devices. They can also inspect equipment, enter data, and manage corrective actions from the Dingo mobile app.
Get the Trakka Asset Health ManagerTM App:
© DINGO Software Pty. Ltd. 2020 ENTERPRISE PREDICTIVE MAINTENANCE SOFTWARE™
SolutionDingo provided critical support in these areas:
• Organized information so the focus was on component health managementand not just monitoring conditions.
• Provided recommended corrective actions to the mine’s local team andtracked issues through resolution.
• Planned condition-based work for mill maintenance windows.
• Served as a continuous source of expertise.
• Provided structure and focus through dashboard KPIs, process control, andbenchmarking.
ResultsThe mine saved $9 million because it no longer needed to buy the two new trucks.
The mill is operating with less than 1% unscheduled downtime in recent months.
Increased availability and extended equipment life saved the mine over $5.5 million per year
95%
90%
85%
80%
75%
70%
Availability Improvement in Year 1
Availability Trend Line
MILL AVAILABILITY
Current
84%
15%
1%
May ‘13
59%
22%
19%
Customer Success Story
Challenge
Normal Warning Critical
Asset Health Improvement• One of the world’s largest copper mines had been using oil analysis,
vibration, and thermography to perform condition monitoring for years.Their fleet health and equipment life were not achieving desired targets.The plan was to purchase two new trucks to supply the productioncapacity needed.
• To address these challenges, the mine partnered with Dingo to implementa holistic condition management program to deliver world-class results.
© DINGO Software Pty. Ltd. 2020 ENTERPRISE PREDICTIVE MAINTENANCE SOFTWARE™
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AMERICAS / EUROPE 8400 E Prentice Ave., Ste 745 Greenwood Village, CO 80111 +1 303 662 9103
EMAIL: [email protected]
ENTERPRISE PREDICTIVE MAINTENANCE SOFTWARE™
Established
1909
2019
Established
1909
2017
For over 25 years DINGO has provided predictive maintenance solutions to asset-intensive industries. We combine deep maintenance expertise with industry leading technology to help companies implement solutions that continuously improve the health and performance of equipment. DINGO currently manages over $13 billion worth of heavy equipment, and our real-world solutions have generated over $700 million in cost savings.
Now is the time to talk to Dingo about the advantages of Predictive Maintenance and improve the productivity and life of your equipment.
Visit DINGO.com or contact us at [email protected] to learn more.
Implement Predictive Maintenance at your Operation
