Copyright 2003 Joseph Greene All Rights Reserved MFGT 124 Solid Design in Manufacturing Product Evaluation for Performance and the Effects of Variation Professor Joe Greene CSU, CHICO Reference: The Mechanical Process, 3rd Edition, David Ullman, McGrall Hill New York (2003) MFGT 124 Copyright 2003 Joseph Greene All Rights Reserved

Chap 11: Product Evaluation Topics Introduction Importance of Functional Evaluation Goals of Performance Evaluation Accuracy, Variation, and Noise Modeling of Performance Evaluation Tolerance Analysis, ISO 9000, and Six Sigma Sensitivity Analysis Robust Design and Taguchi Methods and Design of Experiments Copyright 2003 Joseph Greene All Rights Reserved

Copyright 2003 Joseph Greene All Rights Reserved Summary Product evaluation should be focused on comparison with the engineering requirements and also on the evolution of the function of the product. P-diagrams are useful for identifying and representing the input signals, control parameters, noises, and outputs. Concern must be shown for both the accuracy and variation of the model. ISO 9000 and Six Sigma are essential measurable techniques for modern manufacturing of products. Robust design takes noise into account during experimental design and establishes parameters that are less sensitive to noise factors. Copyright 2003 Joseph Greene All Rights Reserved

Copyright 2003 Joseph Greene All Rights Reserved Introduction Goal of this chapter Compare performance of the product to the engineering specifications from the product design phase. Performance can be measured Mechanical specs. Component and system testing results. Cost specs. Piece cost and cycle time to produce part. Quality specs. How often can product meet mechanical, cost, dimensional specs. Best practices- Table 11.1 (Extension of Table 4.1) Monitoring functional change Goals and modeling of performance evaluation Accuracy, variation, and noise Tolerance and Sensitivity analysis Robust design Value engineering and design for cost Design for manufacturing, assembly, and reliability. Copyright 2003 Joseph Greene All Rights Reserved

Importance of Functional Evaluation Evaluating the performance of the product is essential to the product being used and being sold. Important to track changes made in the function of the product. Important to not add unneeded constraints or functions to product. As product matures, the intended function materializes. Product design needs to keep up with any changes to product or performance tests once released Copyright 2003 Joseph Greene All Rights Reserved

Goals of Performance Evaluation Chap 6 developed engineering requirements based upon needs of the customer. For each requirement a target was set. Now evaluate the product relative to the targets. Measurable targets with numerical values are preferred versus qualitative values. Evaluation of product performance must support these factors. Evaluation must result in numerical measures of product. Evaluation should give some indication of which features of the product design to modify in order to bring target back on spec. Evaluation procedures must include the influence of variations due to manufacturing, aging, and environmental changes. P-diagram P stands for product or process that has some dependent parameters that affect the quality of that feature. Can also use Fishbone diagram to identify cause and effect. Copyright 2003 Joseph Greene All Rights Reserved

Goals of Performance Evaluation P-diagram P stands for product or process that is affected by parameters. Physical dimension, material properties, forces from other systems, forces or motions from system. Manufacturing parameters that affect product. Temperature, pressure, cycle time, operator, machine type. Evaluate system need to assess quality measures. Have input signals that affect quality. Fig 11.2 Other methods include design of experiment. (Later) Product or process Change values or redesign Parameters Targets Quality Measures Input Signals Copyright 2003 Joseph Greene All Rights Reserved

Precision, Accuracy, and Significance Indicates repeatability Accuracy Signifies how close a measurement is to a true value Test Significance Measure of the extent to which the information obtained through the test procedure is a predictor of the performance of the same material in service. Precision Accuracy Precision and Accuracy X X X X X Copyright 2003 Joseph Greene All Rights Reserved

ISO 9000, Six Sigma and Other Quality Mysteries Copyright 2003 Joseph Greene All Rights Reserved

Copyright 2003 Joseph Greene All Rights Reserved Introduction Times are changing for quality In the 1970’s, almost anything manufactured was accepted and shipped. Quality was measured but not well controlled. Quality problems were passed on to customers. Designs didn’t change too quickly. Competition was regional with very little from international. GM had over 50% of the market share of cars. In 1980’s worldwide competition forced higher quality. Many improvements were needed to get higher quality at lowest cost. Labor costs became large and quality per cost ratio In the 1990’s time to market became paramount. Quality measurements influenced product manufacturing. Downsizing, re-engineering, and people changes to meet growing expectations of customers. Highest quality at lowest cost. Quality engineering involves the whole product process from cradle to grave or design concept to manufacturing products to specifications Copyright 2003 Joseph Greene All Rights Reserved

Copyright 2003 Joseph Greene All Rights Reserved Introduction ISO Technical Committee was formed in 1979 To harmonize the increasing international activity in quality management and quality assurance standards. Subcommittee was established to determine common terminology. It developed ISO 8402: Quality-Vocabulary, which was published in 1986. (ASQ published ANSI/ASQ A8402-1994: Quality Systems Terminology. While this document is not an adoption of ISO 8402, it does contain many of the exact terms and definitions contained in ISO 8402.) Subcommittee 2 was established to develop quality systems standards--the result being the ISO 9000 series, published in 1987 (revised 1994). Copyright 2003 Joseph Greene All Rights Reserved

Copyright 2003 Joseph Greene All Rights Reserved ISO 9000 The ISO 9000 series is a set of five individual, but related, international standards on quality management and quality assurance. ISO 9000 requires documentation for everything in manufacturing process. They are generic, not specific to any particular products. They can be used by manufacturing and service industries alike. These standards were developed to effectively document the quality system elements to be implemented in order to maintain an efficient quality system in your company. The ISO 9000 Series standards do not themselves specify the technology to be used for implementing quality system elements. Copyright 2003 Joseph Greene All Rights Reserved

ISO 9000 Requires Documentation RECORDS REQUIRED BY ISO 9001:2000 Copyright 2003 Joseph Greene All Rights Reserved

Copyright 2003 Joseph Greene All Rights Reserved ISO 9000 There are several benefits to implementing this series in your company. For example, it will guide you to build quality into your product or service and avoid costly after-the-fact inspections, warranty costs, and rework. In addition, you may also be able to reduce the number of audits customers perform on your operation. Increasingly, customers are accepting supplier quality system registration from an accredited third-party assessment based on these standards. References J. Lahey and R. Launsby, Experimental Design for Injection Molding, Launsby Publishing, Colorado Springs, CO(1998) http://www.asq.org Copyright 2003 Joseph Greene All Rights Reserved

Copyright 2003 Joseph Greene All Rights Reserved ISO 9000 ISO 9000 provides the user with guidelines for selection and use of ISO 9001, 9002, 9003 and 9004. ISO 9001, 9002, and 9003 are quality system models for external quality assurance. These three models are actually successive subsets of each other. ISO 9001 is the most comprehensive--covering design, manufacturing, installation, and servicing systems. ISO 9002 covers production and installation, and ISO 9003 covers only final product inspection and test. These three models were developed for use in contractual situations such as those between a customer and a supplier. ISO 9004 provides guidelines for internal use by a producer developing its own quality system to meet business needs and take advantage of opportunities. Copyright 2003 Joseph Greene All Rights Reserved

Copyright 2003 Joseph Greene All Rights Reserved ISO 9000 The choice of which model to implement depends on the scope of your operation. For example, if you design your own product or service, you must consider ISO 9001. If you only manufacture (working off someone else's design) you may wish to consider ISO 9002. Finally, if you neither design nor manufacture, you may wish to consider ISO 9003. Copyright 2003 Joseph Greene All Rights Reserved

Copyright 2003 Joseph Greene All Rights Reserved ISO 9000 Purpose of ISO is to promote the development of standardization and related world activities to facilitate the international exchange of goods and services, and to develop cooperation in intellectual, scientific, technological, and economic activity. Introduced in 1987 and adopted in 96 countries. American National Standard Institute (ANSI) is the member body representing the US. Standards are designed to be utilized by manufacturing, process, and services ISO 9000: A road map for use of other standards in this series ISO 9001: A model for use when the company must design and produce a product ISO 9002: A model for use when a company produces a product ISO 9003: A model for quality assurance in final inspection and testing ISO 9004: Provides quality management and quality system guidelines for use by a company in developing and implementing a quality system. Copyright 2003 Joseph Greene All Rights Reserved

Copyright 2003 Joseph Greene All Rights Reserved ISO 9001 ISO 9001: A model for use when the company must design and produce a product Section 4.2.3: Quality Planning The supplier shall define and document the requirements for quality will be met. Quality planning shall be consistent with all other requirements of a supplier’s quality system and shall be documented in a format to suit the supplier’s methods of operation…. The supplier shall give consideration to the following: the preparation of quality plans, the identification and acquisition of any controls, process, equipment (including inspection and test equipment) fictures, resources, and skills that may be needed to achieve the required quality, ensuring the compatibility of the design, the production process, installation, servicing, inspection and test procedures, Copyright 2003 Joseph Greene All Rights Reserved

Copyright 2003 Joseph Greene All Rights Reserved ISO 9004 Reference: http://www.tc176.org/ This document introduces the eight quality management principles on which the quality management system standards of the revised ISO 9000:2000 series are based. The principles are derived from the collective experience and knowledge of the international experts who participate in ISO Technical Committee ISO/TC 176, Quality management and quality assurance, which is responsible for developing and maintaining the ISO 9000 standards. The eight quality management principles are defined in ISO 9000:2000, Quality management systems – Fundamentals and vocabulary, and in ISO 9004:2000, Quality management systems – Guidelines for performance improvements. Principle 1 – Customer focus Principle 2 – Leadership Principle 3 – Involvement of people Principle 4 – Process approach Principle 5 – System approach to management Principle 6 – Continual improvement Principle 7 – Factual approach to decision making Principle 8 – Mutually beneficial supplier relationships Copyright 2003 Joseph Greene All Rights Reserved

Copyright 2003 Joseph Greene All Rights Reserved ISO 9004 Principle 1 – Customer focus Organizations depend on their customers and therefore should understand current and future customer needs, should meet customer requirements and strive to exceed customer expectations. Key benefits: Increased revenue and market share obtained through flexible and fast responses to market opportunities. Increased effectiveness in the use of the organization's resources to enhance customer satisfaction. Improved customer loyalty leading to repeat business. Applying the principle of customer focus typically leads to: Researching and understanding customer needs and expectation Ensuring that the objectives of the organization are linked to customer needs and expectations. Communicating customer needs and expectations throughout the organization. Measuring customer satisfaction and acting on the results. Systematically managing customer relationships. Ensuring a balanced approach between satisfying customers and other interested parties (such as owners, employees, suppliers, financiers, local communities and society as a whole). Copyright 2003 Joseph Greene All Rights Reserved

Copyright 2003 Joseph Greene All Rights Reserved QS 9000 QS-9000 is the shorthand name for "Quality System Requirements QS-9000." It is the common supplier quality standard for Chrysler Corporation, Ford Motor Company, and General Motors Corporation. QS-9000 is based on the 1994 edition of ISO 9001, but it contains additional requirements that are particular to the automotive industry. These additions are considered automotive "interpretations" by the ISO community of accreditation bodies and registrars. QS-9000 applies to suppliers of production materials, production and service parts, heat treating, painting and plating and other finishing services. It does not, therefore, apply to all suppliers of the Big Three. Copyright 2003 Joseph Greene All Rights Reserved

Copyright 2003 Joseph Greene All Rights Reserved Six Sigma Ultimate goal is to ship product with zero defects to the customer. Six sigma recognizes that defects that are generated prior to shipping still represent lost time and materials. Six sigma helps stop variation in product quality at the earliest possible point. The product and process design phase Sigma,, is statistical unit of measure which reflects your process capability. It is the square root of the variance and similar to the standard deviation. The variance is a measure of the spread of the data or how much variability exits. Minimum sigma is best. Six sigma means achieving a desired value plus or minus 3 sigma. It represents 99.99966% of the data on a bell shaped curve. When six sigma quality is achieved, 99.99966% of the products and services are defect-free. Copyright 2003 Joseph Greene All Rights Reserved

Copyright 2003 Joseph Greene All Rights Reserved Six Sigma Six Sigma focuses on variations as the number one enemy in the battle to obtain a high quality product at a low cost. Primary sources of variation are Inadequate design margin Inadequate process control Unstable parts and material If manufacturers are to achieve six sigma quality, they must isolate, control, and continuously reduce variation. Experimentation is needed to reduce variation. Can choose trial and error, or Design of experiments with full factorial or partial factorial designs Design of experiments (DOE) is the best way to control a process and reduce variation. Taguchi DOE is very popular and very efficient experimentation method. Copyright 2003 Joseph Greene All Rights Reserved

Need for Need for Experiments Need to establish cause and effect relationships Home Car repair- Trouble-shooting starting, noise, and braking problems Home repair- Electrical and mechanical problems, cooking, etc. Gardening and lawn maintenance- watering and pesticide use School Studying versus grades performance Attendance versus grade performance Industry Maintenance and trouble-shooting of equipment Effects of moisture, line rate, operators on productivity and quality Trouble shooting production problems for incoming Materials Trouble shooting production problems on Target values for performance or appearance Copyright 2003 Joseph Greene All Rights Reserved

Copyright 2003 Joseph Greene All Rights Reserved Experimental Goals Statistical Accuracy Proper selection of the responses to be measured Determination the number of factors that affect a response The interactions between the factors The number of repetitions per run The form of analysis to be completed Cost Minimize the cost Reduce the number of experiments to the minimum Study the main factors Thoroughly understand the process under study Choose the minimum number of experiments Copyright 2003 Joseph Greene All Rights Reserved

10 Steps to an Effective Design Recognition and Formulation. With the DOE I will solve ________________ The first step is to recognize the problem. A clear statement of the problem can create a better understanding of what needs to be done. It is important that there is a measurable objective, which will produce practical knowledge. After the problems and objective are decided upon, a team can be formed. It is important to put together a diverse team in order to obtain unbiased objectives. Quality characteristics. I want to measure the following: ________________ Quality characteristics used to measure an experiments output influence the number of experiments that need to be carried out. The outputs from these experiments can either be attributed to nature, or variable. Variable characteristics such as dimensions, and strength, generally provide more information than attribute characteristics such as good or bad. Successful experiments should define the measurement process including understanding of how to make the proper measurements. The measurement system must be capable, stable, and robust. Copyright 2003 Joseph Greene All Rights Reserved

10 Steps to an Effective Design 3. Selecting Parameters: I will pick the following parameters with high and low: 1. Parameter = ____________ Low = _______________ High = ___________ 2. Parameter = ____________ Low = _______________ High = ___________ 3. Parameter = ____________ Low = _______________ High = ___________ 4. Parameter = ____________ Low = _______________ High = ___________ 5. Parameter = ____________ Low = _______________ High = ___________ 6. Parameter = ____________ Low = _______________ High = ___________ 7. Parameter = ____________ Low = _______________ High = ___________ 8. Parameter = ____________ Low = _______________ High = ___________ Useful tools for selecting parameters include, Brainstorming, flowcharts, and cause and effect analysis. If important factors are not included in the experiment, then the results may not be accurate. A screening experiment may be useful in identifying the most important parameters 4. Classifying Factors After selecting parameters, the next step is to classify them into control, noise, and signal factors. Control factors are those that can be controlled by an engineer during the production of a product. Control factors are factors that affect target performance, but don't change. These include mold dimensions. Noise factors are those factors that cannot be controlled, are difficult to control, or are too expensive to control. These factors include weather, and operator skill. Copyright 2003 Joseph Greene All Rights Reserved

10 Steps to an Effective Design 5. Determining Levels (See number 3 above) Levels are the value that a factor holds in an experiment. The number of levels used depends on the experiment. For quantitative parameters two levels are generally used unless non-linearity is expected. For qualitative parameters three or more levels are generally used. 6. Interactions Interactions between two design and process parameters exist when the effect of one parameter of the quality characteristic is different at different levels of the other parameter. It must be determined which factors will be the most useful to study. It may be useful to replace an interaction with an additional factor and study it in the first phase of the experiment. Copyright 2003 Joseph Greene All Rights Reserved

10 Steps to an Effective Design 7. Orthogonal Array (MFGT 141 use the Taguchi L8 Array) Orthogonal arrays are a set of tables of numbers created by Taguchi that allow the study of a large number of control and noise factors on the quality characteristic in a minimum number of trials. Put the parameters and levels from number 3 above into the Excel spreadsheet and create the DOE and the order of experiment run. 8. Conducting Phase- Run the experiment Conducting the experiments and recording all of the results is the next step, which must be taken. It is important to minimize the change in noise factors (day and time of running, operator, humidity, environmental conditions around experiment) as much as possible during this step. Copyright 2003 Joseph Greene All Rights Reserved

10 Steps to an Effective Design 9. Analysis- (Use the ANOVA software to determine significance of each parameter, error% of experiment, and best level for each parameter No. 3) After conducting the experiments the data must be analyzed. Statistical analysis should provide sound and valid conclusions. Open the ANOVA.bat file and input the data from the experiment according to: Perform DOE Analysis with ANOVA. 10. Implementation In order to validate experimental conclusions, a confirmatory experiment should be performed. If these results fall inside the range of confidence then they should be implemented into the process.  Experimental design techniques based on Taguchi can offer improvements in product quality and cost. The experimental design methodology advocated by Taguchi emphasizes the importance of quality in the design stage. Using this technique helps to develop products and processes that are robust against sources of variation. Copyright 2003 Joseph Greene All Rights Reserved

Significance of Difference Level Averages Sum Differences from Table Graph Results Analysis of Variance Statistical Measurement Method Measures the total variability in the data measured by the Sum of Squares Separate out the the differences caused by the individual factors Calculates the differences caused by the error Uses the F statistic to calculate the significance Copyright 2003 Joseph Greene All Rights Reserved

Copyright 2003 Joseph Greene All Rights Reserved ANOVA Example Analysis of Variance Note: F Statistic determines significance. If F is greater than a specified value than the factor is significant. Copyright 2003 Joseph Greene All Rights Reserved

Taguchi Experimental Design History of Dr. Genichi Taguchi After WWII, the Japanese initiated a major effort to participate in the world market. The first products were inexpensive, but of poor quality. The Japanese government set up government agencies modeled after US companies (Bell Labs). One such company, Electrical Communication Laboratories of Japan (ECL), hired Dr. Taguchi to reduce the cost of experimentation. Dr. Taguchi developed a series of experiments that resembled partial factorial designs and featured orthogonal (balanced) arrays. The experimental method is called “The Taguchi Approach” Copyright 2003 Joseph Greene All Rights Reserved

Comparison: Taguchi vs. Conventional Experimental Design Traditional experimental designs were introduced by R.A. Fisher in 1920’s in England Limitations of traditional design Limited variety of layouts and difficult data analysis Limited number of variables with many required repetitions Passive approach to interactions. Difficulty in resolving them F statistic only recognized as fully significant. Partial effects are not calculated Taguchi has Multiple layouts and designs and efficient data analysis Minimum number of experiments Active approach to interactions and calculates partial contribution Copyright 2003 Joseph Greene All Rights Reserved

Copyright 2003 Joseph Greene All Rights Reserved Features of Taguchi Orthogonal Arrays Efficient data collection Separated effects from one another Balanced, separable, or not mixed Minimum number of experiments Experimental Designs Two Level- L8, L16, L32 have 8 experiments, 16 experiments, and 32 experiments, respectively Three Level- L9, L27 have 9 experiments and 27 experiments. Data Analysis- Software available Level Averages ANOVA Copyright 2003 Joseph Greene All Rights Reserved

Copyright 2003 Joseph Greene All Rights Reserved Examples Taguchi Design of Experiment for thermoplastic composites Objectives What is the best combination of Twintex composites and GMT? What are the optimum process conditions? Paper for SAE Copyright 2003 Joseph Greene All Rights Reserved

Improving Performance of BMC Bumper Beams DOE Study Evaluate Effectiveness of Prepreg Technology to Selectively Increase Stiffness & Impact Performance Find Optimum Combination of the 2 Materials 4 Variables were Compared vs Static Load : Prepreg Type BMC Glass % Weight Fraction of Prepreg Tonnage of Press

Static Test Setup with a Pendulum Face Moving at a Constant Speed into a Rigidly Mounted Beam

DOE Study TP-BMC Glass Weight Percentage: 20%, 30%, and 40%. .Weight percentage of prepreg: 25%, 50%, and 75%. .Press Tonnage (metric): 450 t, 675 t, and 900 t. .Prepreg type: satin weave (1:1),: twill weave (4:1), and unidirectional (uni);

Select Material Properties of Test Products

Improving Performance of BMC Bumper Beams DOE Study Materials Processed on conventional BMC and GMT Equipment BMC logs were extruded. Prepreg Plates Cut to Shape and heated in GMT oven Projected Area of Part was 370 x 1520 mm, with Nominal Thickness of 8 mm GMT & Prepreg added in Combinations of Fractions of Prepreg to Total Beam Weight 3 Beams in each Combination Molded for Experiment

Experimental Layout for the Taguchi L-9 Note: Equivalent Full Factorial Design would require 81 experiments : Number of Experiments = (levels)Factors = 34 = 81 experiments

Static Load for BMC and Prepreg Experiment Number

Level Averages for GMT/Prepreg

Analysis of Variance(ANOVA) Results Significance Of Each Variable 14985 19.68 28446 18.96 GMT Type 2 82651 41325 54.28 81128 54.08 9531 12.52 17539 11.69 Lay-Up 2 4622 2311 3.04 3100 2.07 e1 0 0 e2 18 13704 761 19795 13.20 Total 26 150007 5770 100

Optimum Levels of Each Variable as Determined from Level Averages Graph

Improving Performance of GMT Bumper Beams Confirmation Run Confirmation Run used same Process Settings Used the GMT product with 30% Chopped Fiber & Each of the Prepreg Materials 5 Beams with Each Prepreg Material were made, plus 5 Control Beams Test Results confirmed C-GMT 30+ Product was Improved by Adding Prepreg Material

Conclusions Comingled thermoplastic prepregs improve the stiffness properties of TP-BMC composites by 15% to 20%. The static load of composite bumper beams increases with up to a maximum of 22% to 25% glass (by volume). Comingled thermoplastic prepregs improve the static bumper performance of TP-BMC composites to a level superior to published results for standard GMT materials. The significant material and processing parameters in this experiment are TP-BMC glass weight percentage, weight percentage prepreg, press tonnage, and prepreg type. The optimum levels for maximum dimensionless static load are: TP-BMC glass weight percentage = 30% Weight percentage prepreg = 75% Press tonnage (metric) = 900 t Prepreg type = Satin