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 second entry in the series.

My last post, Strategies for accelerating the move to simulation-led, systems-driven engineering, 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.

Adoption drivers

In this project, I conducted in-depth, structured but open-ended interviews 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

Adoption constraints

At the same time, there was widespread agreement among all the experts interviewed that these tools and methods are not being brought to bear with anywhere near the breadth or depth that practitioner advocates would like, and that they believe would be greatly beneficial to their organizations and industries.

In probing why this is, the interviews revealed an array of factors constraining broader adoption at present. These range from legacy engineering culture issues, through human resource limitations and constraints imposed by business models and corporate cultures, to entrenched shortcomings in how long-established systems modeling software toolsets have been deployed and applied to the product development process:

  • Legacy engineering culture constraints
    • Conservatism of mining machinery product development culture
    • Engineering practices in long-standardized industries grounded in handbook formulas and rules of thumb
    • Perceived lack of time in schedule to do systems modeling
  • Human resource constraints
    • Low availability of engineers with systems modeling skills
    • Shortage of engineers trained in systems thinking
    • Legacy engineering processes compound shortage of systems-thinking engineers
    • Industry downturns put constraints on professional staff development
  • Business-model and corporate-culture constraints
    • Culture of seeking to mitigate cost and risk by staying with legacy designs instead of advancing and innovating the product
    • Corporate awareness of need to innovate in mining machinery gets stifled at engineering level
    • Low C/VP-level visibility of systems modeling tools in mining machinery
  • Engineering organization constraints on innovating/modernizing their systems modeling technology infrastructure
    • Power users wedded to legacy systems modeling tools
    • Weak integration at many/most points of the engineering digital toolset chain
    • Implementing systems modeling software as a sales configuration/costing aid seen as taking too much time

My next post will detail practitioners’ visions, strategies and best practices for accelerating and institutionalizing the implementation and usage of systems modeling tools and practices in their organizations.

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

Bruce Jenkins, Ora Research

Please Wait...