Potential Failure Modes of Cement Production Process: A Case Study

2019 ◽  
pp. 205-210
Author(s):  
Elita Amrina ◽  
Mutty Oktaviani
Keyword(s):  
Production Process ◽  
Failure Modes ◽  
Cement Production ◽  
Potential Failure

scholarly journals A Factory Analysis on the Proportion of Defects Reduction in The Animal Feed Pellet Production Process using Design of Experiment Analysis

2019 ◽  
Vol 3 (2) ◽  
pp. 26-33
Author(s):  
Keyword(s):  
Production Process ◽  
Failure Modes ◽  
Animal Feed ◽  
Fractional Factorial ◽  
Pareto Chart ◽  
Manufacturing Defects ◽  
Root Cause ◽  
Pellet Production ◽  
Feed Pellet

The aim of this research is to reduce a number of defects during a feed pellet production process to improve customer satisfaction. A factory case study produces the feed pellets for several species such as food for pigs, chickens, and ducks. Production data from January to June 2017 manufacturing found that the manufacturing defects rate were about 3.32%. The data showed that the overall defects originated from different problems; 1) cracked or broken food; 2) high humidity; 3) distorted of product color; and 4) an ingredient error, respectively. Statistical methods, design analysis, and cause analysis techniques e.g. the Ishikawa diagram, Pareto chart, and FMEA (Failure Mode and Effects Analysis) were applied to help the factory to identify the main root cause of the defects and the potential failure modes of the factory case study. Due to an increasing number of complaints, this study only concentrated on the duck feed pellet production process. The study was divided into two parts: finding the root cause of the defects, which are the most critical factors for further analysis, and applying an experimental statistical design to decrease the number of defects during the duck pellet production process. The problem with cracked or broken pellets (dust) was found as the main factor affecting the production defects. Results showed that the main factors contributing to the amount of dusk in the duck feed productions came from three factors as follow: the thickness of die, distance between compression rollers and die, and time and temperature of mill machine needed during compressing the duck feed pellet production. Both the fractional factorial experimental design, 2k and 3k, were used to evaluate the influence of each factor on the duck feed production defects. The results by using the factorial 2K experimental show that the most important variable in duck pellets production were thickness of the die, distance between compression rollers and die, and temperature of mill machine needed during compressing the duck feed pellet production while time was not an interaction effect in this problem. The 3k factorial design was used to determine the interaction effects for the duck pellets production process. The experiment was ran and tested for 3 months. The final outcomes showed a significant reduction of defects from 2.51% to 1.09% (P<0.01). The results indicated that thickness -20 mm. of the die, 0.05 mm of distance between compression rollers and die, and 95 degree Celsius of temperature of mill machine needed during compressing the duck feed pellet production would be the most appropriate set of pelleting machine for the duck production process case study.

scholarly journals An analysis for providing safety in the cooking oil production process through FMECA approach

2016 ◽  
Vol 5 (2) ◽  
pp. 151
Author(s):  
Benedictus Rahardjo ◽  
Bernard Jiang
Keyword(s):  
Production Process ◽  
Failure Mode ◽  
Mode Effects ◽  
Cooking Oil ◽  
Before And After ◽  
Potential Failure ◽  
Corrective Actions ◽  
The Difference ◽  
Criticality Analysis

This study attempts to apply Failure Mode Effects and Criticality Analysis (FMECA) to improve the safety of production system, especially on the production process of an oil company in Indonesia. Since food processing is a worldwide issue and the self management of a food company is more important than relying on government regulations, so the purpose of this study is to identify and analyze the criticality of potential failure mode on the production process, then take corrective actions to minimize the probability of making the same failure mode and re-analyze its criticality. This corrective actions are compared with the before improvement condition by testing the significance of the difference between before and after improvement using two sample t-test. Final result that had been measured is Criticality Priority Number (CPN), which refers to severity category and probability of making the same failure mode. Recommended actions that proposed on the part of FMECA give less CPN significantly compare with before improvement, with increment by 48.33% on coconut cooking oil case study.

scholarly journals Failure Mode and Effect Analysis (FMEA) for confectionery manufacturing in developing countries: Turkish delight production as a case study

2012 ◽  
Vol 32 (3) ◽  
pp. 505-514 ◽  
Author(s):  
Sibel Ozilgen
Keyword(s):  
Failure Mode ◽  
Failure Modes ◽  
Chemical Contamination ◽  
Risk Priority Number ◽  
Analysis Model ◽  
Production Potential ◽  
Effect Analysis ◽  
Potential Failure

The Failure Mode and Effect Analysis (FMEA) was applied for risk assessment of confectionary manufacturing, in whichthe traditional methods and equipment were intensively used in the production. Potential failure modes and effects as well as their possible causes were identified in the process flow. Processing stages that involve intensive handling of food by workers had the highest risk priority numbers (RPN = 216 and 189), followed by chemical contamination risks in different stages of the process. The application of corrective actions substantially reduced the RPN (risk priority number) values. Therefore, the implementation of FMEA (The Failure Mode and Effect Analysis) model in confectionary manufacturing improved the safety and quality of the final products.

A Qualitative Failure Analysis Using Function-Based Performance State-Machines for Fault Identification and Propagation During Early Design Phases

2014 ◽  
Author(s):  
Charlie B. DeStefano ◽  
David C. Jensen
Keyword(s):  
Failure Analysis ◽  
Failure Modes ◽  
Fault Identification ◽  
Manufacturing Processes ◽  
Analysis Method ◽  
Well Performance ◽  
Early Design ◽  
Analysis Methods ◽  
Potential Failure

In a time when major technological advancements are happening at incredible rates and where demands for next-generation systems are constantly growing, advancements in failure analysis methods must constantly be developed, as well. Performance and safety are always top concerns for high-risk complex systems, and therefore, it is important for new failure analysis methods to be explored in order to obtain more useful and comprehensive failure information as early as possible, particularly during early design phases when detailed models might not yet exist. Therefore, this paper proposes a qualitative, function-based failure analysis method for early design phases that is capable of not only analyzing potential failure modes for physical components, but also for any manufacturing processes that might cause failures, as well. In this paper, the proposed method is first described in general and then applied in a case study of a proposed design for a nanochannel DNA sequencing device. Lastly, this paper discusses how more advanced and detailed analyses can be incorporated into this approach during later design phases, when more failure information becomes available.

scholarly journals A Case Study on Recall of used Scopes in the Endoscopy Department by using a Failure Mode & Effect Analysis (FMEA) Proactive Risk Management

2020 ◽  
pp. 13-24
Author(s):  
Zuber Mujeeb Shaikh
Keyword(s):  
Risk Management ◽  
Failure Mode ◽  
Failure Modes ◽  
Risk Priority Number ◽  
Effect Analysis ◽  
Mode Effect ◽  
Potential Failure ◽  
Failure Mode Effect Analysis

Failure Mode and Effects Analysis (FMEA) is the process of reviewing as many components, assemblies, and subsystems as possible to identify potential failure modes in a system and their causes and effects. The study revealed that the Risk Priority Number (RPN) was initially 450 and it has decreased to 90 after implementing all the actions in FMEA.

scholarly journals A DMAIC Integrated Fuzzy FMEA Model: A Case Study in the Automotive Industry

2021 ◽  
Vol 11 (8) ◽  
pp. 3726
Author(s):  
Radu Godina ◽  
Beatriz Gomes Rolis Silva ◽  
Pedro Espadinha-Cruz
Keyword(s):  
Automotive Industry ◽  
Visual Inspection ◽  
Failure Modes ◽  
Expert Knowledge ◽  
Linguistic Terms ◽  
Fuzzy Fmea ◽  
Inspection Process ◽  
Potential Failure ◽  
And Control

The growing competitiveness in the automotive industry and the strict standards to which it is subject, require high quality standards. For this, quality tools such as the failure mode and effects analysis (FMEA) are applied to quantify the risk of potential failure modes. However, for qualitative defects with subjectivity and associated uncertainty, and the lack of specialized technicians, it revealed the inefficiency of the visual inspection process, as well as the limitations of the FMEA that is applied to it. The fuzzy set theory allows dealing with the uncertainty and subjectivity of linguistic terms and, together with the expert systems, allows modeling of the knowledge involved in tasks that require human expertise. In response to the limitations of FMEA, a fuzzy FMEA system was proposed. Integrated in the design, measure, analyze, improve and control (DMAIC) cycle, the proposed system allows the representation of expert knowledge and improves the analysis of subjective failures, hardly detected by visual inspection, compared to FMEA. The fuzzy FMEA system was tested in a real case study at an industrial manufacturing unit. The identified potential failure modes were analyzed and a fuzzy risk priority number (RPN) resulted, which was compared with the classic RPN. The main results revealed several differences between both. The main differences between fuzzy FMEA and classical FMEA come from the non-linear relationship between the variables and in the attribution of an RPN classification that assigns linguistic terms to the results, thus allowing a strengthening of the decision-making regarding the mitigation actions of the most “important” failure modes.

Failure Analysis Case Study of a 1.5 Meter Space Flex Harness

2017 ◽  
Author(s):  
Erick Kim ◽  
Kamjou Mansour ◽  
Gil Garteiz ◽  
Javeck Verdugo ◽  
Ryan Ross ◽  
...  
Keyword(s):  
Failure Analysis ◽  
Failure Modes ◽  
Field Of View ◽  
Area Of Interest ◽  
Air Stream ◽  
Novel Method ◽  
Temperature Controlled ◽  
Non Destructive ◽  
Failure Site

Abstract This paper presents the failure analysis on a 1.5m flex harness for a space flight instrument that exhibited two failure modes: global isolation resistances between all adjacent traces measured tens of milliohm and lower resistance on the order of 1 kiloohm was observed on several pins. It shows a novel method using a temperature controlled air stream while monitoring isolation resistance to identify a general area of interest of a low isolation resistance failure. The paper explains how isolation resistance measurements were taken and details the steps taken in both destructive and non-destructive analyses. In theory, infrared hotspot could have been completed along the length of the flex harness to locate the failure site. However, with a field of view of approximately 5 x 5 cm, this technique would have been time prohibitive.

Case Study and Fault Modeling for Wrong Redundancy Evaluation on DRAM Devices

2007 ◽  
Author(s):  
Martin Versen ◽  
Dorina Diaconescu ◽  
Jerome Touzel
Keyword(s):  
Failure Mode ◽  
Failure Modes ◽  
Fault Modeling ◽  
Mode Analysis ◽  
Root Cause ◽  
Failure Mode Analysis

Abstract The characterization of failure modes of DRAM is often straight forward if array related hard failures with specific addresses for localization are concerned. The paper presents a case study of a bitline oriented failure mode connected to a redundancy evaluation in the DRAM periphery. The failure mode analysis and fault modeling focus both on the root-cause and on the test aspects of the problem.

Methodology for Analysis of Schottky Diode Failures

2010 ◽  
Author(s):  
Bhanu P. Sood ◽  
Michael Pecht ◽  
John Miker ◽  
Tom Wanek
Keyword(s):  
Failure Mode ◽  
Schottky Diode ◽  
Failure Modes ◽  
Schottky Diodes ◽  
Failure Mechanisms ◽  
Forward Voltage ◽  
Fast Switching ◽  
Voltage Drops ◽  
The Common

Abstract Schottky diodes are semiconductor switching devices with low forward voltage drops and very fast switching speeds. This paper provides an overview of the common failure modes in Schottky diodes and corresponding failure mechanisms associated with each failure mode. Results of material level evaluation on diodes and packages as well as manufacturing and assembly processes are analyzed to identify a set of possible failure sites with associated failure modes, mechanisms, and causes. A case study is then presented to illustrate the application of a systematic FMMEA methodology to the analysis of a specific failure in a Schottky diode package.

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