Drive-to-Knowledge

On today’s episode, Ron Miller is joined by FPrin founder Peter Holst to discuss the how of the Knowledge-Driven Product Development process. Peter has shared the eight steps that are associated with the KDPD process and today he dives deep on how to get a successful upfront start to the KDPD process. He explains the importance of dividing your system up into manageable subsystems and how to develop simple simulation models in order to gain greater knowledge of those subsystems in the design environment.

Key Takeaways: 

[2:25] Peter offers a review of the benefits of the KDPD approach over the Design-by-Analogy (DBA) approach.

[6:17] The wearable pump illustrates how to effectively divide a system into subsystems. 

[7:35] Specific subsystems of a wearable pump.

[10:18] The next steps to take and questions to ask after dividing up subsystems.

[11:40]  Some tricks of the trade and a sanity check on fluid power.

[13:15] The objective and benefits of the simple scoping modeling process. 

[16:53] An overview of the benefits of simple scoping modeling for the wearable pump. 

[20:35] First principle simulation models don't require overly complex tools and make systems far less intimidating. 

[22:15]  Advantages of scoping models.

[26:07] The value proposition of KDPD includes avoiding the oversimplifying the complexity of a system and de-risking the entire process. 

[30:08] Wearable pump subsystems could be defined and scoping models completed in a matter of weeks and move the project forward to the next step. 

[31:41] Why do some people avoid doing the work of the KDPD approach? And why you shouldn’t.

[34:35] Skill degradation and how to mitigate it.  

[36:25] A look inside the next episode of Drive to Knowledge — doing the empirical work and integrating these models into full system models. 

Expand Your Knowledge Base: 

FPrin

Case Study: Wearable Pump

KDPD At A Glance — Knowledge-Driven Product Development is:

• A design approach that is heavily based on First Principles thinking and supplemented with model-based design.
• The point of a KDPD approach is to get to a deeper understanding of your design – where you are weak and where you are strong – to focus the right resources on the right problem.
• It typically involves slightly more up-front effort, initially ~ two weeks of additional scoping model effort. The benefit of this effort being that you end-up in a “High Place” with a very good understanding of where your design sits on the response surface and an understanding of what you know, what you don’t know and what are the problems that you are going to have to confront.
• This approach means significantly less effort on the back-end because you have a robust design that you and your design team have greater confidence in.
• Other benefits are less re-work; fewer recalls; lower overall budget; smoother ramp in manufacturing all combining together to yield an overall faster time-to-market.

Guest Bio: 

Peter Holst, Founder, has nearly 30 years of experience in R&D and product development in the field of medical devices and equipment.  He has experience with visual field testers, IV and enteral pumps, surgical robots, cholesterol testers and glucose meters.  He is experienced with drug delivery technologies for liquid drug formulations as well as pulmonary and trans-dermal methods.

Peter is a strong proponent of data driven design methods known as “Lean Engineering” or “Knowledge Driven Product Development”.  With these methods the outcome of the design process is a design that is well understood – by analysis, modeling, and simulation – and well characterized – by directed testing, typically at the sub-system level.  Using this process the design can be typically characterized as “will work” rather than “can work” before making major capital commitments.  Peter has experience in design for high volume manufacturing using various component manufacturing methods including plastic injection molding, metal injection molding, casting, powder metal, sheet metal and machined components.  He also has a background in the design of low volume capital equipment medical mechanisms and systems.

Peter has a BSME from Northwestern University and an MSME with a concentration in dynamics and controls from Santa Clara University.