The use of data is growing in industries where growing is the primary industry. And data mining is unearthing new insights, greater productivity and better lifecycle management—even in an industry where mining is the daily task.
The heavy equipment (HE) industry moves more slowly than others in the industrial space, but the potential for improvement is great. Like the machines themselves, the heavy equipment industry’s move toward a better-connected equipment fleet is gaining forward momentum. Industry leaders have taken notice and are designing equipment that matches their speedier colleagues in other industries.
“In other industries, most companies are further ahead—however, companies in the HE industry are learning fast from their peers in leading industries like aerospace and automotive,” said Hendrik Lange, senior director, Heavy Equipment Industry, Siemens Digital Industries Software. “They have to, as their equipment turns into software-defined products that are highly connected systems of systems. Farms, mines and construction sites become highly data-driven and automated. Compared to five years ago, there is definitely an increased sense of urgency at HE OEMs to move forward in those areas.”
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One of the most dynamic growth areas is model-based systems engineering (MBSE), which creates a digital model of systems that allows for design, simulation, operations, maintenance and lifecycle management of system components. Since the same model is available throughout the organization, the use of MBSE creates a single point of truth for the system and aligns all parts of the organization under a single model.
“There’s been a steady increase in demand for system modeling and model-based systems engineering over the last five years,” said Patrick Ollerton, senior principal for ALM Products at PTC. We see this being driven by increasingly complex products, products with high levels of variability, market shifts to electrification and software-defined products, industry regulations such as DoD 5000.97 and, more recently, updated standards such as SysML v2 with new supporting software tools.”
The HE customer also has seen the value of an MBSE model…and they want more. “Dealing with today’s customer expectations and product trends is one reason,” Lange said. “But they also see that AI delivers opportunities to disrupt their industry once again. The only way to get prepared for AI is to digitalize processes, making sure data is available, has context and is accessible.”
Barriers to Adoption
Change can be elusive, especially if the operations, maintenance and management teams aren’t aligned around the MBSE solution and its potential value.
“Our experience is that a successful implementation mandates an enterprise-wide, top-down change initiative,” Lange said. “HE OEMs are usually large, global corporations that grew both organically and through acquisitions to the industry giants they are today. Across an enterprise, you will have many distributed legacy processes, methods and systems. There are a lot of stakeholders that need to be directionally aligned.”
Ollerton notes that aligning standards within an organization can be a hurdle as well. “The main barriers to MBSE adoption identified by recent market research include a steep learning curve, with software tools, methods and standards such as SysML perceived as difficult to learn and use,” he said. “This perception can result in cultural resistance and a lack of management buy-in. Another challenge commonly raised is integrations, with tool interoperability and model exchange not meeting market expectations.
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“Engineering department acceptance is dependent on the value and output MBSE delivers to engineering processes: generated data and models with traceability enabling immediate usage rather than documents,” Lange added.
He also noted that the sheer size of the equipment involved—everything from massive earth movers to reapers and combines—also can be an issue. “HE is about making highly complex products that come in relatively low volumes in a business that is very cyclical,” Lange said. “Therefore, margins are typically thin, which puts a lot of pressure on product development. For many organizations, it’s not easy to invest time and budget in deploying new technologies while their key priority is also to keep their daily business running.”
To address these, companies such as PTC have been working to develop integrated solutions to create a lifecycle management system. “These inputs have been instrumental in driving PTC’s MBSE strategy and product roadmap for PTC Modeler,” said Ollerton. “We have been striving to solve these problems with tools for easier, simpler modeling, automation for faster diagram creation and easier and robust integrations with other lifecycle tools such as Codebeamer and Windchill, as well as third-party solutions.”