WEG achieves 33 percent reduction in losses with digital maintenance tools
Fuelled by fierce demand for faster and more efficient production, growth in Industry 4.0 spending is predicted to reach $300 billion by 2023. This data comes from IoT Analytic’s Industry 4.0 and Smart Manufacturing report, which states predictive maintenance technologies are among the top Industry 4.0 use cases.
For the last five years, WEG has been developing its own digitalisation portfolio to fulfil this growing demand. Here, the company examines the deployment and success of its predictive maintenance platform, WEG Motion Fleet Management (MFM) at its own facilities.
Prior to launching the WEG Digital business unit in 2019, WEG was exclusively focused on the manufacture of industrial hardware. Headquartered in Brazil and operating branches in 36 countries, WEG has long held a respected status for its 1,200 product lines including motors, drives, generators, transformers and automation products. According to WEG, it has the world’s largest electric motor manufacturing plant and produces a colossal 70,000 electric motors every day across the world.
As a global manufacturer, WEG understands the needs and demands of its customers and their industrial facilities. Among the biggest challenges has been deploying technology to optimise maintenance.
Like many industrial sites, WEG had previously applied a preventive maintenance methodology. As the name suggests, this is the regular, routine maintenance of equipment. Usually, for instance, the bearings in a motor might be relubricated on a six-monthly basis and entirely replaced every five years – regardless of the genuine wear and tear of the asset.
“At our own plant, we were spending a huge amount of time and money on preventative maintenance,” explained Trenton Roncato Juraszek, Mechanical Project Analyst at WEG. “However, we were still experiencing some unexpected breakdowns and subsequent downtime, forcing us to perform costly corrective maintenance. We knew our customers must be experiencing the same problems too, and we knew that better data was the solution.”
WEG began to delve into digitalisation in 2017 with the development of WEG Motor Scan. WEG Motor Scan is a physical sensor that can be attached to a motor – or a peripheral drive, compressor or fan – to monitor its vibration, temperature and performance. The sensor is fixed by a screw on the motor fin, so there is no electrical connection needed.
The flexibility of the sensor was imperative for WEG to source data from legacy equipment. Like most manufacturers, the equipment in the plant varied in age, original equipment manufacturer (OEM) and communication protocol, meaning acquiring data directly was not always possible. This level of scalability was crucial for WEG’s ultimate goal of achieving total asset management through digital technologies.
WEG Motor Scan was launched with WEG Motor Scan Gateway, the technology for sending autonomous motor data to the cloud, either through WiFi, Ethernet or 3G or 4G connection. WEG Motor Scan Gateway was crucial for unlocking remote monitoring of electric motors embedded with sensors. Ultimately, this formed the launch pad for the next phase of WEG’s digital portfolio.
Motion fleet management
After the successful deployment of WEG Motor Scan, WEG developed WEG Motion Fleet Management (MFM) – the tool to take the existing motor performance data to the next level. MFM uses data fed through the WEG Motor Scan Gateway to generate real-time insights into asset performance, providing maintenance teams with a holistic view of the entire facility and its respective assets.
“Through periodic data collection, MFM generates valuable insights to inform maintenance teams on the actual state of plant assets,” explained Juraszek.
“Ultimately, this reduces the need for preventative maintenance schedules and allows maintenance engineers to easily see which assets are showing signs of wear or abnormal behaviour, allowing them to identify critical problems and act accordingly.
The entire platform is designed around usability. It includes customised layouts for navigation for different stakeholders, as well as numerous reports and dashboards with indicators, graphics and historical data. For maintenance engineers, it creates an optimal way to manage workflow, and for plant managers, it provides a plant-wide overview of performance.
Following its development, MFM was deployed at one of WEG’s facilities for electric motors, based in Jaraguá do Sul, Brazil. The site is responsible for the production of 8,000 motors each day and MFM has been imperative in improving the maintenance for this site. Following its success, there have been over 1,378 sensors deployed in only one of WEG’s factory plants to enable MFM.
“The scalability of WEG’s digital portfolio allows us to use MFM to integrate performance data across numerous assets and numerous plants,” continued Juraszek.
“At the WEG compressor centre at our Jaraguá do Sul factory, we integrate data from every single asset, including motors, frequency inverters, pressure sensors, PLCs and gateways. This is allowing us to bring autonomous maintenance operation to this installation.”
Part of this autonomy is enabled through another of WEG’s digital tools, WEG Motor Specialist. Developed after WEG Motor Scan, this tool brings artificial intelligence (AI) and machine learning into the mix to further improve predictive maintenance.
WEG Motor Specialist intelligently learns about the operating patterns of a motor during its operation, noting any indicators of unbalance, misalignment, load and consumption. Rather than relying on an engineer to input the tolerances of a motor or industrial asset, the technology uses historical data to determine when it is performing unusually.
A good example of how this works is coil temperature. The system can provide a prediction of a motor’s internal coil temperature by making calculations based on surface temperature measurements. Should it determine that the coil is at risk of overheating, it automatically advises an engineer to inspect physically the motor and determines exactly what they need to do.
Achievements at WEG
The deployment of MFM and WEG’s digital portfolio at its own facilities has been overwhelmingly positive. Maintenance engineers can work more effectively, plant managers have greater oversight, and downtime has been significantly reduced.
“Following the installation of MFM at WEG’s wire factory based in Brazil, we achieved an annual saving of around $4 million per year,” explained Juraszek.
“This was thanks to a 33 per cent reduction of overall losses that we were previously experiencing due to unplanned downtime. Interestingly, we were also able to postpone some planned investment[s] in new machinery, which benefited the business’s bottom line. Thanks to an improved maintenance plan – repairing and replacing only when we need to – we could make better use of the machinery we already had and extend its lifespan,” concluded Juraszek.
With the creation of the WEG Digital business unit, WEG has demonstrated its commitment to developing and advancing its digital offerings. As with all of its technologies and equipment, WEG follows a vertical approach – using its own motors, drives, technologies and software wherever possible.
Industry 4.0 is a growing market, and as predictive maintenance technologies drive this expansion, WEG will continue to develop new digital tools to support its customers – and its own – needs.
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