China
Africa
Explore chapters and articles related to this topic
Continuous Improvement Toolkit
Published in Tina Kanti Agustiady, Elizabeth A. Cudney, Building a Sustainable Lean Culture, 2023
Tina Kanti Agustiady, Elizabeth A. Cudney
Root cause analysis is the process of finding and eliminating the cause, which would prevent the problem from returning. Only when the root cause is identified and eliminated can the problem be solved. Root cause analysis uses the D-M-A-I-C philosophy as a guide. The steps to root cause analysis are as follows:Define the problemMap the processGather dataSeek for root causes through fishbone diagrams/cause and effect diagramsVerify root causes with dataDevelop solutions and prevention steps including costs and benefitsPilot implementation plansImplementControl utilizing a monitoring plan and process metricsIdentify lessons learned
Painting Problems
Published in Rose A. Ryntz, Philip V. Yaneff, Coatings Of Polymers And Plastics, 2003
Root cause analysis involves the determination of the basic or underlying cause of a defect or problem and the providing of evidence that it is the cause. We know that craters are caused by contaminants, but the root cause of a cratering outbreak may be poor tote cleaning, a contaminated drum, overreduction of the paint so that it flows too much, or a batch of paint that is unusually sensitive to contaminants that always are present. It may be clear that a defect is a solvent pop, but the root cause could be an application problem that causes fat edges or sags that, in turn, lead to pops. Root cause analysis often takes a lot of detective work, experimentation, and documentation. Sometimes it takes longer than it did to solve the problem. The point is that if the true root cause has been identified and removed or fixed, the problem or defect should not occur again.
Incident Investigation or Root Cause Analysis
Published in Edgar Bradley, Reliability Engineering, 2016
Root Cause Analysis: The technique or set of techniques that determines the reason for an incident having occurred. The practise is predicated on the belief that problems are best solved by attempting to correct or eliminate root causes, as opposed to merely addressing immediately obvious symptoms. The term is unfortunate in that, to some, it implies that there is only one main root. Some methodologies actually state this as a fact. Others allow for multiple ‘roots’.
Integral measures and framework for green lean six sigma implementation in manufacturing environment
Published in International Journal of Sustainable Engineering, 2021
Vishwas Yadav, Pardeep Gahlot, Rajeev Rathi, Gunjan Yadav, Anil Kumar, Mahender Singh Kaswan
The purpose of this step is to identify the major causes associated with wastes, emissions and imperfections in the adopted project. In this phase, firstly, value-added, and non-value-added actions have been recognised from the opinions of both customer and business. After this, the process cycle efficiency is directed to equate outstanding standards to detect how much enhancement is required. At the same time, a project is investigated to recognise the bottlenecks points and restraints in an adopted project. After investigation of the project under concern, the causes for emissions, defects and variations are identified. Here tools, like brainstorming, cause and effect diagram (C&E), five why analysis, life cycle impact assessment, failure mode effect analysis (FMEA), etc. are used. The project team here may use brainstorming sessions to recognise possible reasons for the development of these defects. Life cycle impact assessment has been carried out in this stage to measure the possible ecological effects of every process to identify possible sources for high emission levels. Once the potential causes have been investigated, then the study is constricted to find few pre-eminent causes. Tools like Pareto chart, principal component analysis (PCA), hypothesis, brainstorming and regression analysis are also been employed to unearth crucial root causes. Thus, these steps lead to the identification of main reasons for inefficiencies that require to addressed to improve sustainability measures of the project undertaken.
The internet of things for smart manufacturing: A review
Published in IISE Transactions, 2019
Hui Yang, Soundar Kumara, Satish T.S. Bukkapatnam, Fugee Tsung
Process control and decision making: Once a manufacturing process is out of control, the next step is to take optimal actions to bring the system back under control. The action plan depends on a number of steps such as root cause diagnostics, condition prognostics, and system optimization. Traditional methods for root cause diagnostics include engineering-driven statistical models (e.g., stream of variation analysis, probabilistic graph models) (Shi, 2006; Liu et al., 2009) or failure modes and effects analysis (Branksma et al., 2012). Also, physics-driven models can be formulated based on specific failure mechanisms in the manufacturing system. However, they are often not able to match with real data very well and are therefore inadequate to predict system malfunctions and identify root causes. Data-driven models leverage the real-time sensor signals to characterize and model degradation behaviors in the underlying process. A salient advantage is the ability to transform high-dimensional sensor signals into low-dimensional degradation features for condition prognostics (Gebraeel, 2006; Bian et al., 2015).
Determining which of the classic seven quality tools are in the quality practitioner’s RCA tool kit
Published in Cogent Engineering, 2023
A Root Cause Analysis (RCA) is performed to identify the cause of problems and includes actions to establish a definition of the problem, analyze the problem, and find the cause of the problem, so that the problem can be prevented from occurring again (Lee et al., 2018). There are many reasons why an RCA may be needed. For example, Harjac et al. (2008) investigated corrosion of the walls of absorber towers and Cournoyer et al. (2013) investigated cut, torn, and pinched gloves in a safety glove box for a process that involved radioactive material. Alexa and Kiss (2016) describe an RCA to identify the root causes of damaged packaging and Darekar et al. (2013) explain the details of an investigation into the leakage of a vehicle fuel line.