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  Nutek, Inc.     Quality Engineering Seminar, Software, and Consulting ( Since 1987)                          Site: Problem Solving

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Application Support for Production Problem Solving 

Are you in the right place?

What clients to do:

  •  Identify problem
  •  Form project team and appoint leader
  • Contact consultant and schedule experiment planning session

How you would benefit:

  •  Resolve problem
  •  Gather better understanding of the factor influencing outcome
  •  Learn what to do for long term solution

Our comprehensive support includes the following services:

  • Work with your project team and facilitate planning session for experimental investigation.

  • Lay out test plans and describe how to collect test results

  • Analyze results of experiments and identify the most desirable design condition (optimum).

Clients need to carry out experiments as planned and confirm recommendations.

Paper on Problem Solving & Lean      Testimonial on a Production  Application  

    Links to Related Sites & options
  2. Robust System Implementation
  3. Validation Testing Support
  4. Marketing DOE Applications  Support 
  5. Example Case Studies
  6. Free Experiment Design Tips
  7. Five Easy Steps to Solving  (Do it yourself)
  8. Training: Problem Solving by Designed Experiments (2 days)
  9. Follow Recommended Experiment Planning Steps
  10. FREE Training and Reference Materials
[To: Owners, Managers and executive of manufacturing operations:]
Are you experiencing difficulties resolving your critical production and manufacturing problems?
Is your manufacturing and production process suffering from undesirable variations, rework, and rejects?
Are you satisfied with your first time capability?

        Such chronic production problems are like leaky water faucets. Longer you postpone, more it hurts your bottom line. While many problems may be resolved by common problem solving disciplines, there are a few that require special techniques. Fortunately, the solution to most such engineering problems lies in the collective experience and skill of your technical professionals. So, why arenít such problems solved?
        Many such problems do not have a single source. The solution, often, is obtainable by properly adjusting many factors that influence the outcome. To determine the solution, your project team needs to follow a proven structure of thought process and be guided by an experienced facilitator who can help them develop consensus on key technical inputs and confidently rely upon data-driven conclusions derived by conducting economically planned experiments.

[To support clients, we welcome independent associate to work with us on mutually attractive business relation]


REVIEW TESTIMONIALS  (Review Q&A at end of this page)

We support clients at all phases of your project application, be it for proactively optimizing designs (product, process, recipe, marketing literature/web pages, etc) or solving technical problems.

What we can do for you?
Provide application assistance with Problem Solving Using Designed Experiments

Solve production and manufacturing process problems by experimental investigations. Study current performance by running experiments with extreme settings of the controlling variables and carry out analysis of the collected performance data. The ultimate objective will be to secure a robust solution that offers much improved performance of the product and process under investigation. You should definitely consider this approach when the sources of your problem are unknown or otherwise when the problem is suspected to have multiple causes.

Problem solved: First Time Capability (FTC) improved, rejects reduced, and reworks minimized.

How we do it (Outline and Steps):         
    - Provide overview of the DOE/Taguchi technique and solution strategy
    - Facilitate experiment planning
    - Layout experiments and prescribe data Collection Scheme
    - (Project team runs the experiments)
    - Analyze results and recommend solution
    - (Team runs additional experiment to confirm solution)

Support Duration:   Average 3 - 5 days. 


Participants to the experiment planning session are likely to receive an overview of the Taguchi experimental design methods. The team members who take a keen interest in the conduct of the experiments and the subsequent analysis, may further gain insight into the process of determining the optimum condition and identifying factor influences. Team members who wish to develop application level expertise so that they may carry out projects on their own, may attend our public Seminars, read the reference texts and procure Qualitek-4 software for analysis purposes.

There are no minimum educational background requirements for the project team members. However, DOE application is more successful when all team members are committed to working together as a team and are always willing to yield to the consensus decision. Generally, background research about the project, such as ROOT CAUSE ANALYSIS, PARETO DIAGRAM, FISHBONE DIAGRAM, etc., are helpful only when the participants are willing to sacrifice the ownership to such exercises. Such information may be brought to the planning session only when readily available.

Responsibility: All team members must participate in the planning session (1 whole day) and perform other tasks as assigned by the team.

The project team leader provides the overall project coordination. He or she must keep the team members interest in the project alive throughout the project duration. The leader must help formulate consensus on items that are subjectively decided.

Responsibilities/Tasks:  Keep contact with the consultant, form team, communicate with team members, participate in planning session, control project progress, schedule meetings with the consultant, assures timely conduct of the experiments, collect data, and keep team members appraised of the project status.

Roles: Facilitate experiment planning session, designs experiments and analyzes results.

As a participant, how can one be more effective?
1. Keep focus on the project objectives
2. Offer ideas and input when solicited
3. Keep an open mind and accept consensus decisions

How is the problem solved?
By analyzing results of the designed experiments. The facilitator/consultant need not be an expert in the subject product or process. His/her expertise lies in the DOE technique and in working with people at a technical level. Once the designed experiments are carried out, all conclusions are driven by the experimental data.

What should you expect in terms of the size of experiment?
Most common problem solving projects require use of 8, 12 or 16 test conditions. Depending on the costs, a number of samples are tested in each of these conditions. Each samples are then carefully evaluated using one or more criteria of evaluations.

Process Optimization Examples:
Study of Crankshaft Surface Finishing Process,  Adjustment of Transmission Control Cable Parameters,  Study of Plastic Wire Extrusion Process,  Experiment on the Binding Force of a Plastic Product,  Experiment with a Fabric Dyeing Process,   Optimization Automobile Drivability Parameters,  Determination of Optimum Gel Content in Polyethylene Compound,  Study of Heat Treatment Process Parameters,   Minimization of Surface Finish on the Bearing Journals,  Parameter Study of Graco-2 Spray Gun,  Study of Front End Alignment,  Optimization of Instrument Panel Foaming Process,  Aqueous Cleaning for PC Board Soldering,  Process Study of Pinion Bore Honing Process,  Cylinder Core Wash Elimination Study,  Machining Parameters for Minimum Tool Wear,  Optimization Plastic Injection Process,   Study of Effect of Salt Spray on Seal Friction, etc.

Product Design Optimization Examples:
Engine Idle Stability,  Study of Instrument Panel Optimization,  Design Optimization (using FEM model) Study Leading to Selection of Worst Case Barrier Vehicle,   Airbag Optimization Design Study,  Study of Automobile Front Crush Structure Design Parameters,  Fishing Reel Line Roller Design Study,  Automobile Hood Hinge Design Study,  Ultimate Strength Optimization of Bearing Outer Race, etc.

Principal Consultant's Background:
Ranjit K. Roy, Ph.D.,P.E., PMP
(Mechanical Engineering), is president of NUTEK, INC. Dr. Roy has achieved recognition as a consultant and trainer for his down to earth teaching style of Taguchi experimental design methods. He was employed with General Motors Corp. (1976 - 1987, Technical Center, Warren, Michigan, USA.) assuming various engineering responsibilities with his last position as that of Reliability Manager. While at GM, he consulted on a large number of documented Taguchi case studies of significant cost savings.

  When you select us to support you with your DOE/Taguchi applications, we will do the following:

Our Consulting Service - How we facilitate your project application.
At Nutek, we specialize in manufacturing and production problem solving using designed experiments. Our principal application specialist, Dr. Ranjit K. Roy (Mech. Engr.) is well versed in the Taguchi application principles and have over two decades of experience in working with project teams of all sizes and with teams comprising of people from numerous activities. We support your application effort from "cradle to grave". Whether you are interested in solving an immediate problem, or wish to optimize your product/process, our comprehensive consulting services will support you in the following three phases of your projects:

Phase-I    Facilitate Experiment Planning Session (Production problem or design optimization studies)
This is the most critical phase in the application process and must be done on-site with the project team (generally a one-day session). Here our specialist will work with your project team and facilitate the experiment planning session. Your team members need to set aside the entire day (8 AM to 5 PAM) to work with the consultant. The success of the study depends on identifying the appropriate factors for the project through an open and participative brainstorming session. Be aware that this brainstorming may differs from "brainstorming" in conventional sense. Unlike the normal brainstorming session, this meeting  follows a rigid format which is carefully controlled by the facilitator. [Review HOW TO GUIDE for Conducting Experiment Planning Discussions  ]

In most engineering projects, the desired project objectives are generally more than one. Usually these objectives are also measured in different units (say size, weight, surface finish, etc.) of measurements. How do you handle multiple objectives? How do you determine the project parameters that is not just the best for one objective, but better overall for all objectives? We will help you address your individual concerns by consensus weighting and show you a way to formulate an Overall Evaluation Criteria (OEC) which is appropriate for your project objectives. (Time: 1 day with the project team)

Details of services we provide:

  • Facilitate brainstorming session
  • Work with team to help identify and reduce experimental parameters by CONSENSUS decisions
  • Establish performance evaluation criteria
  • Establish scopes of the study (# of experiments, samples required)

Phase-II     Lay out Experimental Plan and Prescribe Data Collection Procedure
Work in this phase is generally done at Nutek. A successful planning session produces all information necessary to layout the experiment. The size of the experiment designed depend on the number of factors selected for the study and their levels chosen. Based on the designed experiment, individual trial conditions are described. These descriptions serve as the work order for each separate experiment setup (called the Trial condition). Along with the prescription for the experiment setups, the method of data collection is also described. (1 - 2 days at Nutek, 1 day on-site is optional. Written report provided)

Specific Services provided:

  • Design experiment
  • Prescribe the recipe of each separate experiments to be conducted
  • Combine multiple evaluation criteria into a single index
  • Defined and the method of data collections, etc.

[The project team follow the prescribed test recipes and completes tests. The team leader forwards the collected test results to Nutek for analysis.]

Phase-III     Analyze Results and Report Findings
Results of experiments carried out contain a vast amount of information. But there are FOUR basic categories of information which even the smallest (L-4 experiment with 1 sample/trial) experiment can yield. Analysis of DOE results contain information such as: (1) Factor Influence (Factor average effect or Main effect), (2) Relative influence of the factors to the variation of results (ANOVA, which is short form for Analysis of Variance), (3) Optimum condition, and (4) Expected performance at the optimum condition. Other types of information like Confidence level, Significance tests, Confidence Interval (C.I.), Loss, etc. are easily obtained with slight additional effort.

For simple experiments, i.e., those with single objectives and one sample/trial condition, calculations are relatively straight forward. With multiple objectives and multiple samples in each trial condition, analysis can become complicated. (Time: 1-3 days at Nutek and 1 day with the project team. Report provided)

Specific Services provided:

  • Perform complete analysis
  • Present the findings (formal report)
  • Recommend the optimum design
  • Predict the expected performance with confidence interval
  • Establish relative influence of factors
  • Determine interactions possibilities between factors

(Click here to review: List of Nutek Client Companies)

Example Application Projects:
(Refer to Example DOE/Taguchi Case Studies included in this site for detail DESIGN and ANALYSIS, and PRESENTATION)

For applications in other areas, visit: Simulation Studies  Validation Testing  Problem Solving   Marketing & Ad



(Click here to review: List of Nutek Client Companies)

Question and Answers

Q1: What kind of problems can be solved by Design of Experiment (DOE) technique?

A1: Any problem or product/process design issues that are suspected to have influence from two or more factors (input variables) will benefit from DOE.

Q2: Why should I apply DOE when there are other simpler problem solving techniques available?

A2:  Use simpler technique that you know to solve problems when you can. generally, if your problem is of technical nature (production process or complex product design) with more than two factors involved, common disciplines of problem solving will not be able to determine a statistically valid solution.

Q3: What are the advantages of using Taguchi version of DOE?

A3:The Taguchi version of DOE is relatively simpler to apply for people with limited background in statistical science. Below are some of the advantages.

  • Relatively smaller size of the experiment
  • Easier to learn and apply
  • Two factor interactions are easily handled in selected orthogonal arrays
  • Mixed level designs are accomplished by simple modification of the orthogonal arrays
  • Noise factor effects are nicely incorporated in design with OUTER ARRAY designs
  • Signal-to-Noise ratio analysis of multiple sample results allows better analysis of variability and robustness
  • LOSS FUNCTION allows translation of improvement in terms of dollars with statistical validity.

Q4: If we were interested in benefiting from the Taguchi DOE technique to solve product or process design issues, how should we go about it?

A4: To learn and apply the technique, you have several options.

  • Retain experienced practitioners to help you with current problems that affect your bottom line.
  • Dedicate time and effort to learn the skill by attending seminar/workshop with focus on application knowledge
  • Build in-house capabilities by whatever means available (Books , software, training, etc.)

Q5:  What level of training or skill building do we need to start applying the technique to solve problems?

A5:  Start with simpler experiments (3 -11 factors). Secure help/guidance from experience practitioners for first few experiments.

Q5: What is a cost effective way, train our own people or secure consulting support?

A5: Depending on your need, select the option. Definitely, starting with a few applications and have success stories to back your training effort is highly recommended.

Q6: If we go for consulting support, what should we expect the consultant to do?

A6: Consultants can help you with all THREE PHASES of the application: (1) Experiment PLANNING, (2) Experiment design, and (3) Analysis of results. Time permitting, you may also receive an overview of the technique and detailed understanding of the activities involved in each step.

Q7: Our process is quite complex, is it possible for consultant to know our process and give us some design recommendation?

A7:A consulting knowledgeable in Taguchi/DOE need not be an expert in your product or process under study. Nor should the consultant participate in major decisions about the project. He or she simply should facilitative and help you walk through the structure of discussions recommended ( ) during the experiment planning session.

Q8:  If we secure consulting support, what kind of time involvement the team members have to offer?

A8: Involvement of the team member will range between 1/2 day to 1 1/2 day. The rest of the work on the project most likely be done by the responsible parties.

Q9: What is time requirement to complete a typical project?

A9:  The project completion time is mainly dictated by the nature of the project and other logistics for conducting the experiments.

Beyond the experiment planning (2 days), the design can be laid out within 2 - 5 days. This allows the experiments (say 4 - 16) conducted. The time for running the experiments will depend on the nature of the project and number of samples tested in each trial condition (cannot be estimated). The final part the consultant provide is analysis service which may take another week.

Q10:  Is there a way to estimate the range of size of experiment that would be involved in our projects?

A10:  Most projects will involve 8 to 12 separate experimental conditions.

Review and print Sample Problem Solving Project Reports: Report-I Report-II