Complaint Analysis Using 8D Method within the Companies in the Field of Automotive

The eight disciplines (8D – Eight Disciplines of Problem Solving) model is a problem solving approach typically employed by quality engineers or other professionals and commonly used by the automotive industry. It is a meticulous process used to solve complex problems and its purpose is to identify, correct, and eliminate recurring problems, and it is useful in product and process improvement. The 8D is a method of analysis that after the detection of an irregularity, identifies and seeks the methods of solving and preventing nonconformity. It is a highly disciplined and effective scientific approach for resolving recurring problems and provides excellent guidelines to identify the root cause of the problem, implement containment actions, develop and then implement corrective actions and preventive actions that make the problem go away permanently. Therefore, the Eight Disciplines of Problem Solving (8D) is a problem-solving tool used usually in response to the removal parameters or known product specifications set by customers and incorporates all the important aspects of problem solving: problem description, root cause analysis, correcting the problem and preventing the problem. The approach establishes a permanent corrective action based on statistical analysis of the problem and focuses on the origin of the problem by determining its root causes. Although it originally comprised eight stages, or disciplines, it was later augmented by an initial planning stage. The 8D method application will result in improved products and processes is structured into eight disciplines, focusing on the synergy of the team. This is a popular method for problem solving because it is reasonably easy to teach and effective.

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Applying Advanced FMEA Methods to Vehicle Fire Cause Determinations

Volume 9: Transportation Systems; Safety Engineering, Risk Analysis and Reliability Methods; Applied Stochastic Optimization, Uncertainty and Probability ◽

10.1115/imece2011-65159 ◽

2011 ◽

Cited By ~ 2

Author(s):

Kerry D. Parrott ◽

Pat J. Mattes ◽

Douglas R. Stahl

Keyword(s):

Automotive Industry ◽

Failure Modes ◽

Illustrative Case ◽

Analysis Tool ◽

Fire Investigation ◽

Root Cause ◽

Product And Process ◽

Illustrative Case Study ◽

Fire Cause

This paper proposes that the advanced Failure Modes and Effects Analysis (FMEA) techniques and methodology currently used by the automotive industry for product and process design can be reversed and used as an effective failure/root cause analysis tool. This paper will review FMEA methodologies, explain the newest advanced FMEA methodologies that are now being used in the automotive industry, and will then explain how this methodology can be effectively reversed and used as a failure analysis and fire cause determination tool referred to as a “reverse FMEA” (rFMEA). This paper will address the application of these techniques and methodology to vehicle fire cause determination. This methodology is particularly suited to situations where multiple potential fire causes are contained within an established area of origin. NFPA 921 Guide for Fire & Explosion Investigations [1] and NFPA 1033 Standard for Professional Qualifications for Fire Investigator [2], often referenced by the fire investigation community, prescribe following a systematic approach utilizing the scientific method for fire origin and cause determinations. The rFMEA methodology is proposed as a fire investigation tool that assists in that process. This “reverse FMEA” methodology will then be applied to a hypothetical, illustrative case study to demonstrate its application.

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Implementasi Konsep A3 Untuk Mengurangi Reject Proses Assembly

Jurnal Teknik Industri ◽

10.22219/jtiumm.vol18.no1.68-73 ◽

2017 ◽

Vol 18 (1) ◽

pp. 68

Author(s):

Rahman Soesilo

Keyword(s):

Problem Solving ◽

Goal Setting ◽

Process Improvement ◽

Assembly Process ◽

Implementation Plan ◽

Root Cause ◽

Plan Action ◽

Implementation Stage

The A3 concept is one of the Toyota tools to propose problem-solving solutions. A3 provides status reports of ongoing activities. This research applies A3 concept to solve reject problem in plastic company assembling process. The reject rate in the assembly process is 15.6%. The implementation stage of A3 concept is identification of problem, targeting, root cause, goal setting, countermeasure, implementation plan, action and follow up. The A3 concept is in line with the Plan-Do-Check-Act (PDCA) process improvement cycle. The results show that using the concept of A3 can reduce the reject Assembly effectively and precisely.

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A Contingency Perspective on Effective Prototyping

Journal of Information Technology ◽

10.1177/026839629300800205 ◽

1993 ◽

Vol 8 (2) ◽

pp. 99-109

Author(s):

Oscar Gutierrez

Keyword(s):

Project Management ◽

Problem Solving ◽

Organizational Support ◽

Linear Problem ◽

Systems Development ◽

Social Mechanism ◽

Contingency Perspective ◽

Future Developments ◽

Product And Process ◽

Selection Of

Current demands on prototyping emphasize increasingly complex and dynamic applications that require sophisticated social mechanism and process enablers. However, much of the emphasis placed today in systems development under prototyping focuses on the supporting technology. The imbalance between product and process perspectives under this approach is explored. A view of prototyping effectiveness is presented in terms of non-linear problem solving, adequate technical and procedural solutions, and organizational support. Implications of this view are presented on the selection of prototyping techniques and on project management concerns. Future developments in prototyping practice are explored.

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A big data-driven root cause analysis system: Application of Machine Learning in quality problem solving

Computers & Industrial Engineering ◽

10.1016/j.cie.2021.107580 ◽

2021 ◽

pp. 107580

Author(s):

Qiuping Ma ◽

Hongyan Li ◽

Anders Thorstenson

Keyword(s):

Machine Learning ◽

Big Data ◽

Problem Solving ◽

System Application ◽

Root Cause Analysis ◽

Data Driven ◽

Cause Analysis ◽

Quality Problem ◽

Root Cause ◽

Analysis System

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Process Improvement of Brake Lever Production Using DMAIC (+)

Volume 3: Design and Manufacturing ◽

10.1115/imece2011-63813 ◽

2011 ◽

Cited By ~ 2

Author(s):

Chittaranjan Sahay ◽

Suhash Ghosh ◽

Pradeep Kumar Bheemarthi

Keyword(s):

Data Analysis ◽

Problem Solving ◽

Process Improvement ◽

Six Sigma ◽

Lean Manufacturing ◽

Cost Effective ◽

Poor Quality ◽

Statistical Process ◽

Automotive Components ◽

The Cost

This work describes a strategy to reduce the cost associated with poor quality, by reducing the parts per million defects by Defining, Measuring, Analyzing, Implementing and Controlling (DMAIC) the production process. The method uses a combination of principles of Six Sigma applications, Lean Manufacturing and Shanin Strategy. The process has been used in analyzing the manufacturing lines of a brake lever at a Connecticut automotive components manufacturing company for reducing the cost associated with the production of nonconforming parts. The analysis was carried out with the help of the data collected on nonconformance parts and the application of phase change rules from DMAIC (+). Data analysis was carried out on statistical process control softwares, MINITAB and SPC XL 2000. Although, the problem of tight bushing existed on only one line of the brake lever assembly, this problem solving approach has solved the tight bushing problems on all assembly and alternates lines in a time- and cost-effective way.

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A Case Study in Extended Value Engineering

Volume 3: 7th Design for Manufacturing Conference ◽

10.1115/detc2002/dfm-34160 ◽

2002 ◽

Cited By ~ 1

Author(s):

R. Anderson ◽

R. Sturges

Keyword(s):

Process Improvement ◽

Cost Reduction ◽

Systematic Approach ◽

Value Engineering ◽

Cost Comparison ◽

Mining Equipment ◽

Analysis Process ◽

Extended Value ◽

Product And Process

Extended value engineering techniques provide an efficient, systematic approach to expose unnecessary costs, spur innovation, and direct efforts toward product and process improvement. Extended value engineering involves the comprehensive application of function diagramming, cost/cycle analysis, process diagramming, and competitive cost comparison. The application of these techniques to a mining equipment manufacturer, specifically to an ore haulage vehicle, is described in terms of cost reduction and manufacturing process improvement.

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