Cut Development Costs in Half
A Case Study
Oxalic Acid Manufacturing Example
Development work is highly unpredictable. Occasionally a major Research and Development project that is expected to take a couple of years is completed in six months or less. More often a small problem, that is expected to be resolved in a day
takes a week or so, and still more often the research target that is supposed to take a month to achieve remains elusive after a year and more.
If this unpredictability is common to research and development it i the hallmark of production problems. So much so that a common adage among production staff is .it is easier to set up a new plant and get quality products like one used to - than to-find out why,the existing plant does not operate as well as in the 'past". Why is the research and development work, and production troubleshooting work so difficult, so frustrating? Is it
really not possible to simplify',and"speed up these work?
Yes it is possible to do that. ' However, before we discuss how this can be- done, let. us discuss' how' the research and development staff or the production troubleshooter operates, what is the methodology, if any.. used by him and what are the advantages and, disadvantages associated with this methodology. The following illustration describes the typical situation as it exists in most plants/industries., While the illustration is chosen with chemical industry in mind, the argument is general and applicable to 'any problem in any industry.
Illustration Part 1
Oxalic Acid Manufacture
Based on a market survey recently published, management of'a medium 'sized chemical company has decided to investigate the technical and economic, feasibility of manufacturing oxalic acid. Accordingly the R & D staff was entrusted with the responsibility to do the literature survey and report the findings.
Literature survey indicated several feasible
and commercial processes. The management decided,
because of economic considerations to try and
experiment with an..untriedprocess involving alkali
fusion of saw-dust. This process gave methanol and
. acetic acid as by-productsand this was an
.important consideration to the company for the
choice of the process.,
R & Dstaif envisaged that the plant would be
operated continuously and as such decided to use a
sim.ilarset up for the laboratory work. An important
question that needed to be answered accu~ately was I
"What is the amount of alkali needed to get.good
;yieldsof oxalic acid?" .
Literature survey coupled with the experience
and judgement of.the R & D statf has suggested tha~
the.v~iables be studied in 'the following rang~' t
~: Ratio of
alkali to saw-dust . ..' 1 I 2. 1 I 5. uni.ts
Saw-dust f.low rate' ... 2; ~ 8. units
.~ .
APpropriate apparatus was set up and three sets. G:!;
experiments were conducted, using a teebnique in.
which only one variable is varied.and studied at.a
time. .
In Set 1 experiments the, ratio was kept fixed at
3.5 units. and.s$,w-dust flow. rate was varied. The coded
data. are shown below..
Mukul is bilingual. He speaks Chemical Engineering and Applied Statistics.
As a Senior R&D Manager, Statistics and Computer-Aided Research at BF Goodrich Chemical, he championed the use of Design of Experiments (DOE) for predictive modeling, performance optimization, scale-up, and quality control.
Currently, he is the Founder and President of FastR&D, LLC, based in Cleveland, Ohio.
Over his career, he has trained nearly 1,000 R&D scientists, engineers, and senior executives. He has led 750 DOE studies across industries including chemicals, food, polymers, plastics, pharmaceuticals, and medical devices. His projects range from scaling up a one-inch fluid bed reactor to an 18-foot production reactor, to optimizing the design of a tiny angioplasty device for renal artery denervation and blood pressure control.
Mukul has advised numerous Fortune 1000 chemical firms on innovation, rapid new product development, and managing NPD as a structured business process.
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