The topic was delivered by Dr. V.E. Annamalai, Head of Department – SSN College of Engineering, Chennai.

1. Knowledge Partner
Fhyzics Business Consultants Pvt.Ltd.
Dr. V.E. Annamalai
Head of Department – SSN
College of Engineering,
Chennai
Developing a First-Time-Right Culture
in Product Development

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www.pdma-india.in

3. Developing a First-Time-Right
Culture in Product Development

4. 4
Context & Disclaimer
These are born out of personal experience of managing a Group of R&D personnel in a Grinding
wheel Industry.
The simple steps followed to achieve sustainable New Product Sale, comprised more of
behaviour correction than of tools and techniques. Hence the name Culture!
Knowledge management principles were deployed at every stage to measure and document slips
in design.
This is a Practitioner’s view and not that of an Expert.

5. PART-1
The Backdrop on Metrics & Culture
5

6. 6
What metrics we use for NPD?
We are used to “End of Design” Metrics like
• Time to Market
• New Product Sales
• Number of products developed
Interestingly, none of these metrics throw light on the efficiency of the R&D person-for
example, no one knows
How many times the design failed in lab!
There is no “In-Process” Metrics for NPD

7. 7
The Culture
Under the cover of “Confidentiality” designs are not offered for any audit with openness.
The designer has the luxury to fail “n” number of times. This will be captured only as Less Sale of
NPD or more time to market, which are complex metrics that do not pin point the designer and
his mistakes.
All available tools like QFD , DFM etc can be subjectively manipulated by the designer. He can
continue to do what he wants to do, and still convince others that he follows tools!

8. PART-2
The Need for “In-Process” Metrics
8

9. 9
The decision points in Product Development in R&D
Stage 1 – Design Selection based on info from Marketing team
Stage 2 – Concept Selection- Individual perceptions on what would work
Stage 3 – Lab Testing- Decision on Clearance test
Stage 4 – Design Finalization - Based on performance, ignoring cost
Stage 5 – Scaling Up - Shopfloor equipment with relaxed Specs
Stage 6 – Release norms Different from Design clearance norms

10. 10
Initiation Stage - Design Selection Accuracy F1
Someone in marketing team sees a better product at customer end and brings you an
information on expected performance targets.
How effective are we in converting this into design parameters?
Do we have a strong understanding of what recipe does what performance? (in spite of a
good QFD !)
Big umbrella , small umbrella, what do they mean?
Have you ever attempted to remove anything from a recipe?
Door when squeaks, we add oil..

11. 11
Concept Selection Stage – Effect Prediction Accuracy F2
In Reverse Engineering, what is the accuracy of our analysis?
What are we measuring? How accurate is our evaluation?
What are we NOT measuring? How accurately do we guess this?

12. When some parameter in performance is expected, how do we choose alternate designs?
Do we have proof of what works in a given situation?
Do we extend what worked in some other product to this product?
Is it Expertise?
Is it Courage?
Is it Experimenting at the cost of customer?
Concept Selection Stage – Effect Prediction Accuracy F2
12

13. 13
Has there been a loss while producing new products?
Did we inform Manufacturing team about this?
Has there been complaints where new product worked less than existing product?
Has there been instances where new products did not deliver what was expected?
Concept Selection Stage – Effect Prediction Accuracy F2

14. 14
Lab Testing Stage – Inaccuracy due to irrelevant testing F3
What is the difference between hot idlis and cold idlis?
We always taste the hot idlis and leave the customer to taste the cold idlis...
Our Testing is when product is just manufactured (fresh).
Customer tests the product after several days, months, years.
Do our ingredients remain stable with time? Can we say that for products with polymers
and resins?
Can we test as our customer sees the product? How to do it?
Accelerated test , ageing test etc.

15. 15
Design Finalisation Stage –
Factor of non sustainable design – F4
When three designs work, R&D ego is to offer the highest performing product.
Do we apply factors of Manufacturing ease? (DFM?)
Do we apply factors of cost and contribution?
Are we aware that competitor also is at work and may have better designs up his
sleeve?
Are we ready with a second version right now?

16. 16
Shopfloor Manufacturing Stage –
Uncertainty factor in scaling up F5
Initial trials manufactured in R&D equipment are with closer tolerance.
When order quantity is high and cannot be accommodated in R&D facility, it is manufactured in
shopfloor facility.
Shopfloor specs are with wider tolerance.
The impact of wider process tolerance on performance goes unnoticed.

17. 17
Field Trial Stage – Change in Release Norms F6
New product was tested for performance when it was manufactured in R&D for some parameter or
many parameters.
Shopfloor products are released with some other parameter or with only some parameters being
tested.

18. 18
The combined impact of all the Factors
F1 – Design Selection Accuracy (0.9)
F2 – Effect Prediction Accuracy in Design (0.81)
F3 – Inaccuracy due to non-relevant testing (0.729)
F4 – Difficulty due to non-sustainable design (0.656)
F5 – Uncertainty in Scaling up (0.59)
F6 – Change in Release Norms (0.531)
Even if we are 90% efficient in each stage, our FTR is 53 % only

19. 19
The approach to a possible solution
All these six factors were considered in detail and a simple methodology was
developed.
In spite of QFD and DFM tools, it was the attitude of the individual to follow
rules, that mattered.
The approach was based on the behavioral response of R&D team in every
Design decision situation.
These are described in Part 3
The major shift was
from “end of design” metrics to “In-Process” metrics.

20. PART-3
The Approach to FTR Culture
20

21. 21
The Approach
There are four major reasons for a Product Failure
1.Not knowing the Customers’ needs
2.Variation in Lab and shopfloor conditions
3.Inability to handle scaling up
4.Inability to quick-serve the next level product

22. 22
The Approach
1.Consider a Failure in design as a Deviation.
2.Measure the number of instances the deviation occurs.
3.Analyse the cause for the deviation.
4.Develop methodologies to prevent recurrence of deviations.

23. 23
The four step Approach
This eliminates the ambiguity caused by someone who saw and described the requirement
to you.
A reference product can be checked and assessed for direct design parameters as well as
implied needs.
1.Providing a product that works
1a) start with a reference product

24. 24
Develop List of what concept worked in which product earlier.
Pick concepts from this list only.
1.Providing a product that works
1b) Use proven concepts only
The four step Approach

25. 25
For every concept, follow proper recording .
Make the product with that change
Evaluate the performance
Verify whether expected parameter in performance has been improved.
If it works, add to Design Guideline.
If it does not work, add to Do Not Do list.
The four step Approach

26. 26
A preferred numbering system would be
DG/year/serial number (for successful concepts)
DND/year/serial number (for failed concepts)
DG-Design Guidelines; DND-Do Not Do
The four step Approach

27. 27
Format for Design Failure Analysis - DFA

28. 28

29. 29
1c)develop an in house test method
Cannot afford to use customer as testing ground.
Simulations are not effective unless we have a correlation between simulation and actual results.
In house testing must replicate similar usage pattern at customer end.
For long tests, better to develop ageing tests or accelerated life tests.

30. 30
Step 2 - Making your Design Saleable
Can we work like the Chinese?
A Rs.100 product locally manufactured is matched with a Rs.40 selling price at local
market.
We just cannot quickly shoot it out. Demands a lot of work (and time) to counter it.
This time is enough to make the sale they wanted to make, even if they exit afterwards.

31. 31
Step 2 - Making your Design Saleable
High performance versus performance per unit cost.
Competitor is also working continuously.
The moment you introduce a product, he is going to introduce his second and better
version. Are you going back to redesign for cost purposes?
Many new products suffer by not being cost effective and marketing ends up offering heavy
discounts on New products.

32. 32
D1
Performance ok; contribution poor
D2
Performance close; contribution
acceptable

33. 33
D3 Performance poor; contribution
high
D4 Performance acceptable
contribution high
Clear D4
Work on D2

34. 34
Step 2 - Making your Design Saleable
Y axis can be selected to represent any performance parameter of the product.
Better to use the parameter the customer is looking for-not your usual performance
parameters.
If customer is looking for surface finish, then the products must be compared on surface
finish .

35. 35
Step 3 – Retaining the performance during Scaling up
Know the inconsistency band before releasing the product.
The performance of the product must be recorded in the extreme combinations of allowed process tolerances.
If temperature is 200+/- 10, test at 190 and at 210 deg C.
If density is 35+/- 0.5 g/ci, test at 34.5 and at 35.5.
Also use lowest density at lowest temperature and highest density at highest temperature -the major possible
variations.

36. 36
Step 3 – Retaining the performance during Scaling up
The results show the possible performance variation in the existing shopfloor specification
tolerance of the processes involved.
If this variation is permitted, send to next stage.
If not, redo the design .
This stage is called “Clearing for Performance Band”

37. 37
Clearance for Performance band

38. 38
Step 4 – Getting ready to handle complaints
4a) Keep track of the indicators
A defect located inside the factory is a loss.
A defect detected outside the factory is a complaint.
Monitor the losses happening during manufacture of new products and address those issues- these
are potential issues that may turn up as complaint from customer.

39. 39
Step 4 – Getting ready to handle complaints
4b) Hold on to the design that worked initially
In the unlikely event of a complaint on NPD subsequent supplies, almost everyone starts suspecting the
design.
Complaint indicates some attribute of the new product that was not available in the subsequent supplies.

40. 40
Step 4 – Getting ready to handle complaints
Since Design has not changed between first and next supply, it must be the manufacturing slips that must
have created the trouble.
Check the process changes and only if you are convinced, allow a design change .
Never ever correct complaint in new product by a design change- you are making the mistake of
introducing another totally new product without all the previous stage check
Points.

41. 41
Format for Process Failure Analysis - PFA

42. 42
I have not changed anything, says the Manufacturing person-maybe he is right. But the
number of processes and the combination of process tolerances are too complex to
understand the possible number of ways by which something can go wrong.
The defect could be due to one kiln intermittently shooting off into high temperature. Without
correcting it, changing the design would never help.
4b) Hold on to the design that worked initially

43. 43
4c) Know the possible abuse of your product
A Customer may use your product in more than one way- in many ways you never even assumed
possible.
Share autos- cleaners- clinging on to doors in open condition- definitely was not a design
parameter.
Hinge was designed to open and close with ease, not to bear the cleaner's weight!

44. 44
4d) Be ready with the next design
Competitor also has research teams like you.
They are not going to keep quiet.
As soon as you introduce , even before you get confirmed bulk orders, they may introduce an even
better product.

45. 45
4d) Be ready with the next design
Have you had experience where first supply was excellent and next supply was considered not so
good- your production records showing everything okay?
It just means the competition has improved their product silently and in comparison, our second
supply has been rated poor.

46. 46
4d) Be ready with the next design
Same product development may come back within three months. No point starting all over again.
Better to have at least one design “up the sleeve”.
Best option is to use Taguchi method of Robust design and release the second best product of
your design that matches customer requirement.
Reserve your first best design, to counter competition’s reaction to your introduced New product

47. PART-4
The Impact of FTR Culture
47

48. 48
The Impact on New Product Sales
New Product Sale
0
500
1000
1500
2000
1 2 3 4 5 6
Year
SalevalueinRs.lakhs

49. 49
The Impact on Product Development Time
Product Development Time
0
2
4
6
8
10
1 2 3 4 5 6
Year
Months

50. 50
The Impact on First Time Right Designs
FTR %
0
10
20
30
40
50
60
70
80
1 2 3 4 5 6
Year
FirstTimeRight%

51. 51
The Impact of First Time Right Designs on development time
FTR vs Product development time
0
1
2
3
4
5
6
7
8
9
10
20 38 48 53 65 72
FTR %
Timeinmonths

52. 52
The Impact of First Time Right Designs on NPD Sales
NPD sale vs FTR
0
500
1000
1500
2000
20 38 48 53 65 72
FTR %
SaleinRs.Lakhs

53. 53
1.Providing a product that works
a)Start with a reference product
b)Use only proven concepts
c)Develop an in-house test method
2.Making your design saleable Use Contribution versus performance graph
3.Retaining the performance during
scaling up
Use Consistency Clearance after estimating the
inconsistency band
4.Getting ready to handle
complaints
a)Keep Track of the indicators
b)Hold on to the design that worked initially
c)Know the possible abuse of your product
d)Be ready with the next design
The Four Step process to FTR

54. Thank you