Machine identification of potential manufacturing process failure modes based on process constituent elements

2022 ◽  
Vol 51 ◽  
pp. 101491
Author(s):  
Zhongyi Wu ◽  
Hong Zhang ◽  
Weidong Liu ◽  
Zhenzhen Li ◽  
Weijie Zheng
Keyword(s):  
Manufacturing Process ◽  
Failure Modes ◽  
Process Failure ◽  
Constituent Elements

Reverse Fishbone Diagram: A Tool in Aid of Design for Product Retirement

1996 ◽  
Author(s):  
Kosuke Ishii ◽  
Burton H. Lee
Keyword(s):  
Failure Modes ◽  
Graphical Representation ◽  
Environmentally Conscious ◽  
The Past ◽  
Advanced Planning ◽  
Process Failure ◽  
Fishbone Diagram ◽  
Useful Life ◽  
Definition Of ◽  
Central Tool

Abstract This paper describes a schematic representation of product retirement specification that aids in design for recycling and reuse. In the past decade, a graphical representation of the assembly process, called the assembly fishbone diagram, has effectively assisted engineers to conduct design for assembly (DFA) and process failure modes and effects analysis (FMEA). On the other hand, environmentally conscious manufacturing requires engineers to make advanced planning for product retirement. This study investigates the use of the reverse fishbone diagram to model the disassembly and reprocessing sequence of a product at the end of its useful life. An industry-provided student project guided us to an initial definition of the reverse fishbone diagram that effectively led the students to analyze the recyclability and make practical redesign suggestions. The diagram is continuously adding more rigorous definitions and promises to be a central tool for evaluation of recyclability in a simultaneous engineering setting.

Thermal–Hydraulic Performance Analysis for AP1000 Passive Containment Cooling System

2013 ◽  
Author(s):  
Yu Yu ◽  
Shengfei Wang ◽  
Fenglei Niu
Keyword(s):  
System Reliability ◽  
Nuclear Power ◽  
Failure Modes ◽  
Cooling System ◽  
Natural Circulation ◽  
Hydraulic Performance ◽  
Reactor Power ◽  
Physical Parameters ◽  
Cold Source ◽  
Process Failure

In order to improve the safety of new generation nuclear power plant, passive containment cooling system is innovatively used in AP1000 reactor design. However, since the system operation is based on natural circulation, physical process failure — natural circulation cannot establish or be maintained — becomes one of the important failure modes. Uncertainties in the physical parameters such as heat and cold source temperature and in the structure parameters have important effect on the system reliability. In this paper, thermal–hydraulic model is established for passive containment cooling system in AP1000 and the thermal–hydraulic performance is studied, the effect of factors such as air temperature and reactor power on the system reliability are analyzed.

Challenges and Methods in the Quantification of Design Errors and Solution Elements

2004 ◽  
Author(s):  
Lawrence P. Chao ◽  
Kosuke Ishii
Keyword(s):  
Design Process ◽  
Life Cycle Cost ◽  
Quality Function Deployment ◽  
Failure Modes ◽  
Spatial Distance ◽  
Risk Priority Number ◽  
Design Elements ◽  
Process Failure ◽  
Temporal And Spatial ◽  
Process Level

To error-proof the design process, tools such as Design Process Failure Modes and Effects Analysis and Project Quality Function Deployment mitigate risk through thorough understanding of the consequences of both the process-level errors that can occur and the solution elements that mitigate them. However, the quantification of design errors and prioritization of other elements are complicated by the temporal and spatial distance of the decisions from the end-result. This paper discusses measures for design elements in the context of process-based analysis, including the design errors, tasks, and project resources. The Risk Priority Number is the standard measure of criticality of failure modes and their effects. However, alternatives to the traditional RPN have emerged in forms such as expected and life-cycle cost as well as QFD-based techniques. The paper explores the benefits and challenges of these traditional and new measures and concludes with a discussion into converting between the measures.

Lab-scale evaluations on formation of products of incomplete combustion in hazardous waste incineration: influence of process variables

1997 ◽  
Vol 36 (11) ◽  
pp. 219-226 ◽  
Author(s):  
G. Mascolo ◽  
L. Spinosa ◽  
V. Lotito ◽  
G. Mininni ◽  
G. Bagnuolo
Keyword(s):  
Failure Mode ◽  
Failure Modes ◽  
Waste Incineration ◽  
Process Variables ◽  
Thermal Failure ◽  
Process Failure ◽  
Toxic Organics ◽  
Laboratory Investigations ◽  
Hazardous Waste Incineration ◽  
Products Of Incomplete Combustion

Laboratory investigations have been carried out to study the influence of process failure modes on organics emission during the incineration of hazardous sludge. The thermal, temporal and fuel-oxidant mixing failure modes were tested. They were simulated by holding the first combustion temperature at 400°C and varying the after-burning one between 600 and 1100°C, the after-burning residence time between 1 and 3 s and the excess air between 30 and 160%. Results showed that the thermal failure mode is the most important factor controlling the number and concentration of emitted organics leading to the formation of over 70 compounds at after-burning temperature of 600°C. At higher after-burning temperatures emissions are controlled by the fuel-oxidant mixing failure mode and, only when the after-burning is 800°C and the oxygen is 160% over the stoichiometric value, by the temporal failure mode. Based on results obtained some suggestions for reducing emissions of toxic organics in full-scale incinerators are given.

scholarly journals A Case Study on Improving Intensive Care Unit (ICU) Services Reliability: By Using Process Failure Mode and Effects Analysis (PFMEA)

2016 ◽  
Vol 8 (9) ◽  
pp. 207 ◽  
Author(s):  
Taraneh Yousefinezhadi ◽  
Farnaz Attar Jannesar Nobari ◽  
Faranak Behzadi Goodari ◽  
Mohammad Arab
Keyword(s):  
Intensive Care ◽  
Human Error ◽  
Failure Modes ◽  
Classification Model ◽  
Group Discussions ◽  
Team Members ◽  
Acceptable Risks ◽  
Process Failure ◽  
Potential Failure ◽  
Fmea Method

<p><strong>INTRODUCTION:</strong> In any complex human system, human error is inevitable and shows that can’t be eliminated by blaming wrong doers. So with the aim of improving Intensive Care Units (ICU) reliability in hospitals, this research tries to identify and analyze ICU’s process failure modes at the point of systematic approach to errors.</p><p><strong>METHODS:</strong> In this descriptive research, data was gathered qualitatively by observations, document reviews, and Focus Group Discussions (FGDs) with the process owners in two selected ICUs in Tehran in 2014. But, data analysis was quantitative, based on failures’ Risk Priority Number (RPN) at the base of Failure Modes and Effects Analysis (FMEA) method used.<strong> </strong>Besides, some causes of failures were analyzed by qualitative Eindhoven Classification Model (ECM).</p><p><strong>RESULTS:</strong> Through<strong> </strong>FMEA methodology, 378 potential failure modes from 180 ICU activities in hospital A and 184 potential failures from 99 ICU activities in hospital B were identified and evaluated. Then with 90% reliability (RPN≥100), totally 18 failures in hospital A and 42<strong> </strong>ones in hospital B were identified as non-acceptable risks and then their causes were analyzed by ECM.</p><p><strong>CONCLUSIONS</strong>: Applying of modified PFMEA for improving two selected ICUs’ processes reliability in two different kinds of hospitals shows that this method empowers staff to identify, evaluate, prioritize and analyze all potential failure modes and also make them eager to identify their causes, recommend corrective actions and even participate in improving process without feeling blamed by top management. Moreover, by combining FMEA and ECM, team members can easily identify failure causes at the point of health care perspectives.</p>

Risk Evaluation Approach in Failure Mode and Effect Analysis of Automotive Headlamp Assembly

2014 ◽  
Vol 564 ◽  
pp. 72-76
Author(s):  
Shukriah Abdullah ◽  
Aziz Abdul Faieza
Keyword(s):  
Failure Mode ◽  
Failure Modes ◽  
Assessment Tool ◽  
Action Plan ◽  
Technical Problem ◽  
Assembly Process ◽  
Preventive Action ◽  
Effect Analysis ◽  
Evaluation Approach ◽  
Process Failure

Headlamp assembly entailed a complex assembly process and error in assembled can result in technical problem and higher reject rate at the end of the assembly process. A study has been conducted, in one of the automotive headlamp assembly in Malaysia, where there are numerous defect detected during the assembly process, such as metal spacing missing, wrong model housing, wrong sticker affix, wrong orientation with a total of 80% defects detected. Currently the headlamps are assembled with no dimensional control, results in high physical nonconformity product. The main objective of this project is to identify potential failure in headlamp assembly process. The approach used was risk assessment tool which is Process Failure Mode and Effect. This work also developed the corrective action plan for accurate ranking of Failure Modes by Risk Priority Number-based method and implement it to the process assembly. The result showed that there was increased of 5% in preventive action and 4% increment of the detection action

Assembly FMEA: A Simplified Method for Identifying Assembly Errors

2003 ◽  
Author(s):  
Steven Kmenta ◽  
Brent Cheldelin ◽  
Kosuke Ishii
Keyword(s):  
Artificial Intelligence ◽  
Failure Modes ◽  
Electronic Circuits ◽  
Manual Assembly ◽  
Manufacturing Defects ◽  
Novel Technique ◽  
Analysis Process ◽  
Simplified Method ◽  
Process Failure ◽  
Assembly Defect

Manual assembly errors are a significant source of manufacturing defects. Therefore, an efficient method is needed to identify and alleviate potential assembly defects. Process Failure Modes and Effects Analysis (Process FMEA) is one technique used to anticipate, evaluate, and resolve potential manufacturing and assembly issues. However, performing FMEA is widely considered to be tedious and time-consuming, and not always worth the effort. In response, many researchers have attempted to automate FMEA using Artificial Intelligence (AI) to make it less arduous. Unfortunately, automated techniques are limited to systems with predictable behaviors (e.g., electronic circuits) and are rarely used on unpredictable processes such as manual assembly. “Assembly FMEA” is a novel technique developed specifically to identify manual assembly errors. Assembly defect levels are related to assembly complexity, which can be estimated using “Design for Assembly” (DFA) time penalties. Hence, Assembly FMEA uses a series of DFA-related questions to elicit potential assembly defects. The questions help to focus, standardize, and expedite the FMEA process. Assembly FMEA quickly identifies a large number of assembly errors with significantly less effort than conventional FMEA. This paper describes the Assembly FMEA procedure and illustrates its use on a conceptual design and on an existing product.

Sign in / Sign up

Export Citation Format

Share Document