This guest contribution on Innovation Intelligence is an abridged version of a series of blog posts written by Bruce Jenkins, President of Ora Research, an engineering research and advisory service. Maplesoft commissioned him to examine how systems-driven engineering practices are being integrated into the early stages of product development, the results of which are available in a free whitepaper entitled System-Level Physical Modeling and Simulation. Maplesoft’s Maple and MapleSim software are available through the Altair Partner Alliance.

Discussions of how to bring simulation to bear starting in the early stages of product development have become commonplace today. Driving these discussions, is growing recognition that engineering design in general, and conceptual and preliminary engineering in particular, face unprecedented pressures to move beyond the intuition-based, guess-and-correct methods that have long dominated product development practices in discrete manufacturing. To continue meeting their enterprises’ strategic business imperatives, engineering organizations must move more deeply into applying all the capabilities for systematic, rational, rapid design development, exploration and optimization available from today’s simulation software technologies.

System-level physical modeling and simulation software empower engineers and engineering teams to begin studying, exploring and optimizing designs in the beginning stages of projects—when product geometry is seldom available for 3D CAE, but when informed engineering decision-making can have its strongest impact and leverage on product development outcomes. Then, properly applied, systems modeling tools can help engineering teams maintain visibility and control at the subsystems, systems and whole-product levels as the design evolves through development, integration, optimization and validation.

I proposed that Maplesoft commission me to further investigate these issues through primary research among expert practitioners and engineering management, with emphasis on the off-highway equipment and mining machinery industries.

You can download the white paper here.

Adoption drivers

In-depth, structured but open-ended interviews were conducted with some half-dozen expert practitioners at leading manufacturers, including both engineering management and senior discipline leads. These interviews identified the following key technological factors as well as business and competitive issues driving adoption and use of systems modeling tools and methods at current levels:

• Fuel economy and emissions mandates, powertrain electrification and autonomous operation requirements
• Software’s ability to drive down product cost of ownership and delivery times
• Traditional development processes often fail to surface system-level issues until fabrication or assembly, or even until operational deployment
• Detailed analysis tools such as FEA and CFD focus on behaviors at the component level, and are not optimal for studies of the complete system
• Engineering departments/groups enjoy greater freedom in systems modeling software selection and purchase decisions than in enterprise-controlled CAD/PDM/PLM decisions
• Good C/VP-level visibility of systems modeling tools, especially in off-highway equipment

Potential adoption accelerators

After identifying present-day adoption drivers, I sought to learn practitioners’ visions, strategies and best practices for accelerating and institutionalizing the implementation and usage of systems modeling tools and practices in their organizations.

I was strongly encouraged to find a wealth of avenues and opportunities for exploiting enterprise business drivers, current industry disruptions, and related internal realignments and change-management initiatives to help drive introduction—or proliferation—of these technologies and their associated new ways of working into engineering organizations:

• Systems modeling essential to compete by creating differentiated products
• Mechatronics revolution in off-highway equipment
• Industry downturns and disruptions create opportunities for disruptive innovation
  • Opportunities to leverage change in underlying industry competitive dynamics
  • Mining industry down-cycle creates opportunity to innovate, find new ways of working
  • Some manufacturers are using current down-cycle in mining industry to change their product innovation strategy
• Strategies of manufacturers pursuing disruptive innovation
  • Best odds are in companies with deep culture of continually inculcating new skills into their people, and rethinking methods and work processes
  • Downsizing in off-highway equipment manufacturers may push them to seek more systems-level value-add from their component suppliers
• New technology opportunities inside manufacturers ready to move more deeply into systems modeling
  • Opportunities in new/emerging industries/companies without legacy investments in systems modeling tools and libraries
  • Best practice for introducing systems modeling: start with work process, then bring in software
  • Capitalizing on engineering’s leeway and autonomy in specifying systems modeling software compared with enterprise-standard CAD/PLM tools
• Systems modeling technology advances anticipated by practitioner advocates
  • Improving software integration, interoperability, data interchange
  • Improving co-simulation across domain tools
  • Better, more complete FMI (Functional Mock-up Interface) implementation/compliance
  • Higher-fidelity versions of FMI or similar

The white paper detailing the findings of this research is intended to offer guidance and advice for implementing change, as well as documentation to help convince colleagues, management and partners that new ways of working exist, and that the software technologies to support and enable them are available, accessible, and delivering payback and business advantage to forward-thinking engineering organizations today.

My hope is that this research finds utility as a practical, actionable aid for engineers and engineering management in helping their organizations to adopt and implement—or to strengthen and deepen—a simulation-led, systems-driven approach to product development.

You can download the full white paper reporting our findings here.