Asset maintenance is one of the most pressing issues for high-reliability organizations (HROs) such as hospitals, plants, warehouses, and telecom stations. Unplanned downtime and high maintenance costs make businesses adopt a smarter way to asset maintenance. Thus, businesses are moving from a reactive to proactive approach to maintenance that is at the core of predictive and preventative maintenance. Gone are the days when technicians wait until the equipment fails and only then start repairing it. Now, organizations focus more on predicting and preventing issues. In industries like manufacturing, telecom, and healthcare, which live by strict laws and processes, predictive maintenance and preventative maintenance play a crucial role in maximizing reliability, minimizing repairs, reducing long term costs, and saving people’s lives.
Why are companies adopting preventive maintenance? What is the difference between reactive vs predictive vs preventive maintenance? What are the use cases of preventive maintenance in manufacturing, telecom, and healthcare? Here come the answers.
Main types of maintenance: Reactive vs Predictive vs Preventive
Many companies across industries have confirmed that maintenance costs represent a sizable share of operating costs. Thus, organizations strive to implement a well-thought-out maintenance strategy to ensure that their assets work in the most productive manner possible. There are three major types of equipment maintenance: reactive, preventive, and predictive maintenance. Each strategy has a different bearing on budget and productivity.
Reactive maintenance (Run-to-failure) is a thing of the past. In industries like manufacturing, telecom, and healthcare where the unplanned downtime can cost not only a lot of money but also reputation or even life, it is very dangerous to allow assets to run to failure. Although this method is less time-consuming, requires no planning and less initial cost, it isn’t an option for high-reliability organizations like hospitals, plants, and telcos. Reactive maintenance can take place in case of redundant, easy-to-repair, and non-critical assets (for example light bulbs).
Preventive Maintenance takes a planned or scheduled approach to asset maintenance. It is one of the most popular and effective maintenance methods. According to the 2019 Maintenance study report, 78% of businesses undertake a preventive maintenance strategy. The main aim is to prevent the breakdown or degradation of a piece of equipment, component, or spare part. For implementing such maintenance, teams get the instructions from original equipment manufacturers (OEMs) or have to consider the history of equipment and keep track of its past failures. They identify the frequency in which the equipment can have a breakdown and require repair/service and schedule a maintenance plan accordingly. Preventive maintenance can be time-based or usage-based. For example, periodic inspection of elevators every 2 years or the review of the fleet vehicles when they reach a certain mileage.
Preventive maintenance is efficient when it is done right. It requires a solid strategy in place and the use of the right tools. Tons of paper documents and spreadsheets are no longer an option. With the help of software and electronic gadgets, you can automate maintenance tasks, get instant access to asset information and preventive maintenance protocols.
Here are the best practices you need to follow to achieve success with preventive maintenance:
- Conduct a review of your assets, processes, and people.
- Estimate the ROI you will get with preventive maintenance.
- Identify maintenance metrics you need to track: Mean Time Between Failure (MTBF), Mean Time to Repair (MTTR), Overall Equipment Effectiveness (OEE), etc.
- Set up key performance indicators (KPIs).
- Make use of technology: computerized maintenance management system (CMMS), facility management software (FMS), mobile phones, tablets, cameras, QR scanners. etc.
Predictive maintenance (PdM) is based on constant real-time condition monitoring and utilizes AI & ML to predict issues. Specialists take the existing data or gather data across different parameters such as temperature, vibration, humidity, light, etc. with the help of IoT sensors. Then, they analyze this data by running algorithms and predict when a failure may occur. This way, maintenance is performed on machines only when it is actually required.
Please note: There are two more approaches to how asset maintenance gets done: with the help of Reliability Centered Maintenance (RCM) and Computerized Maintenance Management System (CMMS). RCM is a corporate-level maintenance strategy designed to match individual assets with the maintenance techniques most likely to deliver cost-effective outcomes. CMMS is a piece of software that stores data about the maintenance performed on equipment, machinery, and other assets for the purpose of providing data that can be used to increase efficiency and decrease costs.
If to compare all the three main methods of asset maintenance, according to Google Trends, preventive maintenance is a bit ahead in the hype cycle having passed its peak levels around 2004. Preventive maintenance seems to be a happy medium in terms of maintenance and repair costs. Reactive maintenance is highly costly. According to estimations by Marshall Institute, the reactive approach costs companies up to 5 times more than proactive types of maintenance. Predictive maintenance is also cost-consuming as it requires the use of expensive technology and experienced personnel to do data analytics. Nonetheless, the adoption of predictive maintenance is growing. Very often preventive maintenance is combined with predictive maintenance to cover use cases when it is not possible to establish a standard for the breakdowns of an asset and it can fail randomly. Also, predictive maintenance is hard to implement when there is no record of planned maintenance activities. In this case, preventive maintenance serves as a good basis for kicking off predictive maintenance. So, in the majority of industries, including telecom, manufacturing and healthcare, predictive and preventive maintenance go hand in hand.
What is preventive maintenance in manufacturing?
The manufacturing industry relies heavily on equipment and technology. With the rise of Industry 4.0, Big Data, AI, Ml, CV are transforming industrial production processes from design to manufacturing and asset maintenance. In recent years, predictive maintenance in manufacturing is gaining more and more popularity. But the empirical approach based on experience and manufacturer’s recommendations also brings its value. In manufacturing, preventive maintenance and predictive maintenance complement each other and are used depending on the risk factors and the nature of the equipment failure (whether it is random or not). This allows manufacturers to save costs on predictive maintenance in cases when it is not necessary and reduce over-maintenance and no-fault-found events that cause service standstill and cost companies a lot of trouble.
Case study #1: Preventive maintenance to improve asset performance and decrease maintenance costs
Fluke Corporation is a US-based company that manufactures, distributes, and services electronic test tools and software for measuring and condition monitoring. The company employs about 2,400 people and has distributor and manufacturer representative channels in more than 100 countries.
N-iX has helped Fluke Digital Systems to improve asset maintenance and significantly decrease maintenance costs. Software developers have ensured preventative maintenance of the equipment based on real-time asset data. They also have guaranteed security and reliability of applications in the cloud.
Thanks to the innovative technology stack, Fluke solutions can meet high scalability and customization goals. By incorporating industry best practices, N-iX has helped Fluke Corporation empower organizations to intelligently monitor the equipment with the help of software, reducing unplanned downtime.
What is preventive maintenance in healthcare?
Technology has penetrated into every aspect of today’s life and the healthcare industry is no exception. Telemedicine, imaging, diagnostics can’t make it without software, hardware, and electronic devices. Handheld computers capable of accessing patient histories and life support biomedical devices are on the frontline of the healthcare industry. Thus, asset management is one of the acute issues in the healthcare sector. HCOs are striving to make it both efficient and cost-effective.
In healthcare, preventive maintenance has great weight as it helps avoid service interruption due to missing service checks. Healthcare is a highly regulated industry and all the equipment should comply with certain standards and undergo regular inspection. This is where preventive maintenance comes in handy. CMMS, smart QR code scanners and GPS tracking technology help notify, find, and plan the assessment of devices such bladder scanners, blood pressure monitors, wheelchairs, etc., which are due for inspection or repair.
Case study #2: Preventive maintenance to enable cost savings, solution reliability, and seamless operation
WEINMANN Emergency is a German-based medical technology company founded back in 1874 that employs more than 200 people. It develops medical equipment ranging from emergency cases and backpacks to suction machines, oxygen systems, portable ventilators and defibrillators. The company distributes its products in Germany and in more than 120 other countries around the world.
Thanks to telemetry support that the N-iX team has helped to develop, it is possible to prevent device failures that are related to defibrillation and monitoring. On the basis of service, event, and verbose technical logs, maintenance specialists can detect problems with device sensors, its core components, or an expired service check date. It allows specialists to monitor equipment health based on real-time asset data and plan regular inspections to prevent equipment failure. For instance, a team of maintenance specialists arrives on the scene, runs diagnostics, and either repairs the device before it goes out of order or sends it for the service check to avoid a service standstill.
What is preventive maintenance in telecom?
Routine preventative maintenance definitely has its place in the telecom industry. Telcos focus as much on rigorous planning and strict processes as they do on the Industry 4.0 technologies. The benefits of preventive maintenance in telecom are numerous. It helps avoid service-level agreement (SLA) breaches, network faults, and equipment failure. The examples of preventive maintenance in telecom are the following:
- Regular network bandwidth checks;
- Network security assessment;
- Verification and certification of service-level agreements;
- Validation of antenna orientations and corrections if required
- Network hardening and network densification;
- Vegetation management, etc.
As telcos expand and become more complex, the telecom industry faces more and more issues with network maintenance and performance. 5G and IoT only add to the ever-increasing complexity of the network. Thus, telcos can't do without big data, AI, ML, and data analytics for network monitoring and maintenance. Here we have featured the case to give you an example of when it is beneficial to implement intelligent technologies in asset maintenance. With the help of predictive maintenance, a global in-flight internet provider has managed to significantly decrease operational expenses and no-fault-found rate.
Case study #3: Predictive maintenance vs preventive maintenance
Gogo is a global provider of in-flight broadband Internet with over 20 years of experience and more than 1,000 employees. Today, Gogo has partnerships with more than 16 commercial airlines, and it has installed in-flight connectivity technology on more than 2,900 commercial aircraft and over 6,600 business aircraft.
Gogo has partnered with N-iX to improve the operation of the equipment and ensure high speed of the in-flight Internet. Together with our client, we completely migrated Gogo data solutions to the AWS cloud and shut down its costly on-premises infrastructure. Our team built a unified AWS-based data platform that collects and aggregates data from 20 different sources and can process up to 3 TB of streaming data per day.
With Data Science and Machine Learning algorithms, we developed models for predicting satellite antennas failures and antennas health monitoring. The solution provides interpretable reasoning behind each recommendation. For example, we identified that when antifreeze liquid is applied, and the plane does a couple of flights, the fluid gets inside the antenna and affects its performance. Therefore, the recommendation was to add an additional layer of protection from the fluid. As a result, the solution allows Gogo to significantly save operational expenses on penalties to airlines for the ill-performance of Wi-Fi services. The no-fault-found rate was reduced by 75%, thus saving costs on unnecessary removal of equipment for servicing. Predictive analytics allows predicting the failure of antennas (>90 %, 20-30 days in advance) and ensures servicing of the in-flight equipment at the most suitable time, for example, when there are no flights scheduled for a plane.
How can N-iX help you with asset maintenance?
- N-iX boasts an internal pool of 2,000+ experts.
- N-iX is trusted in the global tech market: the company has been listed among the top software development providers by Clutch, in the Global Outsourcing 100 by IAOP for 4 consecutive years, recognized by GSA UK 2019 Awards, included in top software development companies by GoodFirms.co, and others.
- N-iX partners with leading global companies such as WEINMANN Emergency, Fluke Corporation, Gogo, and more to help them implement predictive and preventive maintenance.
- N-iX is a Select AWS Consulting Partner, a Microsoft Gold Certified Partner, a Google Cloud Partner.
- We have profound cloud expertise and employ 400+ cloud engineers. Our cloud experts are certified by industry leaders.
- N-iX experts have proven experience working with such technologies as computer vision, AI & ML, robotics, etc.
- Our expertise in cloud computing includes cloud-native services, on-premise-to-cloud migration, cloud-to-cloud migration, as well as multicloud and hybrid cloud management.
- We offer professional DevOps services, including Cloud adoption (infrastructure set up, migration, optimization), building and streamlining CI/CD processes, security issues detection/prevention (DDOS & intrusion), firewall-as-a-service, and more.
- N-iX has broad data expertise to design different kinds of data solutions: Big Data / Data Warehouse / Data lake development, Business Intelligence, Data Science, Artificial Intelligence & Machine Learning, etc.
- N-iX has been named No. 72 on the 2020 CRN Fast Growth 150 List for the substantial growth and performance over the previous two years.
- N-iX is compliant with PCI DSS, ISO 9001, ISO 27001, and GDPR standards.