This article and the subsequent white paper link was written by Mike Keer and the Product Realization Group team.
New Product Introduction consists of people, processes and technology, which together provide a formal methodology for a product’s transition from engineering design to volume manufacturing. A subset of the product lifecycle process, which covers the entire lifecycle of a product from concept to end of life, NPI’s primary focus is on a product’s beta, pilot, and general availability (GA) stages.
Here are seven best practices for deploying a strong NPI strategy:
- Use Concurrent Engineering
- Mitigate Risks
- Employ Design for Excellence (DFX)
- Leverage Rapid Prototyping and Accelerated Life Testing
- Adhere to Agency and Environmental Compliance Requirements
- Learn from Prototype and Pilot Builds
- Deploy Scalable Business Systems
Successful new product development (NPD) involves the art of balancing schedules, resources, and costs to enable products that launch on-time, with desired performance and at the right cost. Inevitably, trade-offs and risks must be made along the way. Companies that manage these trade-offs and risks consistently outperform their competitors.
On May 17, we created a panel of industry experts to look at how to identify all the risks in development, and shares their knowledge of the latest emerging risks. The panelists offer a variety of perspectives – ranging from Mechanical and Electrical Design, Product Reliability and Parts Fabrication. Practical issues of how upstream design decisions impact downstream performance, quality and costs will be explored.
You can download a copy of the presentation at: Managing Design Risk
Or you can download a copy off the PRG website at: Managing Design Risk-PRG
In the presentation, you will learn about:
- Five tips for risk mitigation
- Managing constraints and trade-offs
- Concurrent engineering and communications
- Emerging risks
- Reliability considerations
If you have any tips or recommendations, please respond to this blog with your inputs. We’d love to hear from you.
Competitive advantage is driven by cost reduction. However, cost reduction is a by-product of the efforts to improve quality and reduce time of availability.
Reducing manufacturing changeover time (setup reduction -SMED) accomplishes this. It provides the benefits of quality and time reduction while developing flexibility to respond to customer changes.
How well are you doing this? What kind of insight and advantage are you giving your customers? Understand what are the tasks to do this.
Contact the author for more direction in this area!
An adaption of the Functional Safety standards IEC 61508 and IEC 26262 by the European Union brought a new life into slowly fading activity of reliability prediction. Both reliability prediction and reliability demonstration are now key parts of many product development programs, however despite phonetic similarity those two have little in common as well as the result they generate.
While reliability prediction is an analytical activity often based on mathematical combination of reliabilities of parts or components comprising the system; reliability demonstration is based on product testing and is statistically driven by the test sample size. Therefore the obtained results could drastically differ. For example, a predicted system failure rate of 30 FIT (30 failures per billion (109) hours) would corresponds to a 10 year reliability of 99.87% (assuming 12 hours per day operation). In order to demonstrate this kind of reliability with 50% confidence (50% confidence is considered low in most industries) one would need to successfully test 533 parts (based on binomial distribution) to the equivalent of 10 year field life. Needless to say that this kind of test sample is prohibitive in most industries. For example in the automotive electronics the test sample size of 23 is quite common, which roughly corresponds to 97% reliability with 50% confidence.
The natural question is: how do you reconcile the numbers obtained from reliability prediction with the numbers you can support as part of reliability demonstration?
The answer is: I don’t believe that you can.
You can make an argument that reliability demonstration produces the lower estimate values. Additionally the test is often addresses higher percentile severity users, thus the demonstrated reliability for the whole product population will likely be higher. However, in most of the cases the gap will remain too wide to close. This is something, which reliability engineers, design teams, and most importantly customers need to be aware of and be able to deal with as part of the product development reality.
What does the audience think? We’d love to hear your opinions on this.
SMTA Conference on Soldering and Reliability – May 15-18, 2012, Toronto
Ops A La Carte’s Peter Arrowsmith will be giving a presentation at this conference on "Improving Product Reliability Using Accelerated Stress Testing".