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Bruce Jenkins is 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. In this series of blog posts, Mr. Jenkins discusses the results of his research.

This is the third entry in the series.

My last post, System-level physical modeling and simulation: Adoption drivers vs. adoption constraints, described my firm’s research project to investigate the contemporary state of adoption and application of systems modeling software technologies, and their attendant methods and work processes, in the engineering design of off-highway equipment and mining machinery.

In this project, I interviewed some half-dozen expert practitioners at leading manufacturers, including both engineering management and senior discipline leads, to identify key technological factors as well as business and competitive issues driving adoption and use of systems modeling at current levels.

After identifying present-day adoption drivers as well as current constraints on adoption, finally 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
    • Some managements willing to take radical corporate measures to replace old-thinking engineering staff with “systems thinkers”
    • 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.

Bruce Jenkins, Ora Research
oraresearch.com

Bruce Jenkins is 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. In the coming weeks, Mr. Jenkins will discuss the results of his research in a series of blog posts.

This is the first entry in the series.

Discussions of how to bring simulation to bear starting in the early stages of product development have become commonplace today. Driving these discussions, I believe, 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.

Unfortunately, discussions of how to simulate early still fixate all too often on 3D CAE methods such as finite element analysis and computational fluid dynamics. This reveals a widespread dearth of awareness and understanding—compounded by some fear, intimidation and avoidance—of system-level physical modeling and simulation software. This technology empowers 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.

As part of my ongoing research and reporting intended to help remedy the low awareness and substantial under-utilization of system-level physical modeling software in too many manufacturing industries today, earlier this year I produced a white paper, “System-Level Physical Modeling and Simulation: Strategies for Accelerating the Move to Simulation-Led, Systems-Driven Engineering in Off-Highway Equipment and Mining Machinery.” The project that resulted in this white paper originated during a technology briefing I received in late 2015 from Maplesoft. The company had noticed my commentary in industry and trade publications expressing the views set out above, and approached me to explore what they saw as shared perspectives.

From these discussions, 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. In this research, focused not on software-brand-specific factors but instead on industry-wide issues, I interviewed users of a broad range of systems modeling software products including Dassault Systèmes’ Dymola, Maplesoft’s MapleSim, The MathWorks’ Simulink, Siemens PLM’s LMS Imagine.Lab Amesim, and the Modelica tools and libraries from various providers. Interviewees were drawn from manufacturers of off-highway equipment and mining machinery as well as some makers of materials handling machinery.

At the outset, I worked with Maplesoft to define the project methodology. My firm, Ora Research, then executed the interviews, analyzed the findings and developed the white paper independently of input from Maplesoft. That said, I believe the findings of this project strongly support and validate Maplesoft’s vision and strategy for what it calls model-driven innovation. You can download the white paper here.

Bruce Jenkins, Ora Research
oraresearch.com

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