Root Cause Analysis & Manufacturing Troubleshooting

Modern, complex assemblies can fail due to a failure or defect in a single component or through an interaction between multiple components in a system.The cause is often related to a components inputs (e.g., raw material, processing conditions, loading conditions, environment, etc.). Starting with the failed assembly or defective product, Exponent specialists combine sound engineering judgment with troubleshooting methods to efficiently determine the root cause of the failure.Crucial activities for troubleshooting include: Problem Definition: Systematic definition of inputs to reduce total troubleshooting time Identification of inputs via production experience and engineering judgment Identification of Correlations: Searching for values or combination of values that are associated with the failure or defect Applying troubleshooting experience to achieve efficient, cost-effective searching Validation: Recreation of the failure or defect to confirm causation Augmenting organizational knowledge through sharing success and documenting lessons learnedExponent specialists can guide an organization through each of these activities. Troubleshooting methods and tools we can apply include: Root Cause Analysis Structured Brainstorming Methods Ishikawa (aka Fishbone) Diagrams 5 Whys Is/Is Not Analysis 8D Problem Solving

Process or Product Improvement

Improving a process requires an understanding of the process. This understanding must be both broad and deep. Exponent has the expertise to provide deep process understanding from a broad range of viewpoints: Scientific and engineering expertise in the underlying process physics Statistical analysis of process behavior Quality assurance techniques Project and team managementWe have demonstrated the ability to use this knowledge to implement process improvements in many industries including aerospace, automotive, consumer products, energy, and biomedical.In addition to deep theoretical knowledge, Exponent brings practical industrial experience to bear on process improvement projects. We have expertise in the most effective tools and methods for process improvement used in industry today. These include: Statistical Process Control (SPC) Engineering Process Control Measurement System Analysis (Gage R&R) Design of Experiments Six Sigma Techniques Lean Manufacturing Value Stream Mapping Just-In-Time DeliveryMany of these tools and techniques can be used to improve products as well as the processes used to produce them. Exponent can assist in efforts such as: Design Improvement Requirement Definition, Including Quality Function Deployment (QFD) Failure Mode and Effects Analysis (FMEA) Reliability Improvement and Analysis

Design Quality

Relying on testing to identify quality products is inefficient and wasteful. Modern quality systems are based on the tenet that quality should be designed in, not tested in. Philip Crosby summarized this well: Quality has to be caused, not controlled [Philip Crosbys Reflections on Quality, 1996. Foundational principles for designing-in quality include: Customer Focus: Customers define quality-incorporate that definition into designs upfront Delighting customers requires insight into their motivations Scientific Approach: Good decisions are based on valid data and rigorous scrutiny Sustainable solutions require a systemic approach Teamwork: Successful projects engage and respect all stakeholders Disciplined team & project management yields resultsExponent specialists can guide an organization in making these principles operational. Methods and tools we can apply include: Design for Six Sigma Failure Mode and Effects Analysis: DFMEA, PFMEA Failure Mode Avoidance Robust Design Design of Experiments Structured Innovation

Sampling or Test Plan Development

Sampling provides qualitative and quantitative information concerning a process or product. Although desirable, 100% sampling is rarely possible due to costs, time, or destructive testing methods. Thus, it is important to develop a sampling plan that balances the information obtained from the tests with the costs and time to conduct the test. Important considerations for developing a sampling plan include: Understanding the Specific Application: Applying engineering judgment to facilitate selection of appropriate variables and their assumed distributions (e.g., Gaussian, Poisson) Identifying the right values to measure in order to reduce the number of tests Sample Size Selection: Information is not free - sampling plan should consider costs of each observation Too few samples may fail to identify false negatives Complexity Reduction: Applying designed experiments to make testing more efficient Designing appropriate accelerated tests to reduce test length and costExponent specialists can help organizations develop good data collection and analysis techniques to measure the quality of the raw materials, components, products, and assemblies. We can guide an organization through creation of a sampling or test plans by applying specific methods such as: Power and Sample Size Calculations Design of Experiments (DOE) Test to Failure Accelerated Testing Acceptance Testing (e.g., ASQ, ANSI, ASTM, Mil-Std methods)Quality System Assessment

The International Organization for Standardization (ISO) has outlined quality principles and the procedures for implementing a quality management system in ISO 9000, ISO 9001 and other documents. In many fields such documents serve as the basis for regulation. However, it is not uncommon for organizations to attain ISO certification but still be plagued by serious quality challenges.Ultimately the quality of products and processes produced by a manufacturer is a result of its entire manufacturing system. Successful organizations recognize that quality is not the responsibility of a single department or activity; rather it is the responsibility of the entire organization from the executives to the production floor; from the planners and marketers to the sellers and distributors.Quality needs to be managed as system. A quality system is more than the documents that define it. A good quality system is characterized by: Adherence to well defined standard operating procedures and policies that minimize variation in production and throughout the organization Proactive identification of potential problems and customer-oriented solutions Discipline and prioritization of resources to implement and document solutions on a sustained basisExponent engineers and scientists are ideally suited to help companies transition their approach to quality from a reactive stance of constant firefights and quality escapes to a proactive position where problems are identified, corrected, and permanently prevented from recurring. Methods and tools Exponent can apply include: Quality system assessment and benchmarking Quality System Inspection Technique (QSIT) Corrective and Preventive Action (CAPA) systems Statistical data collection and analysis tools

Manufacturing Data AnalysisAdvances in computing technology and the consequent abilities to create, store, and access increasingly larger volumes of data in modern business and science have created new opportunities and challenges. Data mining refers to the application of visual and statistical methods to turn seemingly disparate data streams into potentially useful information. Foundational principles for analyzing large quantities of manufacturing data include: Visualization: Insight is accelerated through data visualization Graphical analyses of multi-dimensional data is very powerful Data Mining: Discovering previously unknown patterns and correlations Reliability improvement and elimination of failure modes Variability Reduction: Understanding causal relationships will lead to greater consistency Improved product consistency delights customersExponent specialists can assist an organization in making these principles operational. Methods and tools we can apply include: Graphical Tools Dimensionality Reduction Classification, Regression, and Clustering Analyses Statistical Methods

ashok 9538891127