Development of FMEA Method with the Purpose of Quality Assessment of Can Stock Production

Klochkov, Yury; Its, Alena E.; Васильєва, І. В.

doi:10.4028/www.scientific.net/kem.684.473

Cited by 28 publications

(4 citation statements)

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“…The need to define the maximum material workability temperature in the cutting process occurred in the course of developing the methodology to assess the assembled metal-cutting tools' application quality [1][2][3][4][5][6] with account of the tools' reliability properties [7], which were defined by the updated FMEA methodology [8]. The methodology is based on the essential extreme change in the processed materials' mechanical and physical parameters depending on their temperature.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Possible Application of Temperature Dependences of Processed Materials’ Physical and Mechanical Properties to Define the Maximum Workability Temperature

Vasilega

Zyryanov

2017

KEM

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The results of experimental studies of the different machinability group materials’ characteristics, including tool steel DIN C125W, heat-resistant steel (C - 0.1%, Si - 0.6%, Cu - 0.3%, W - 0.1%, Mn - 0.4%, Ni - 23%, P - 0.01%, Cr - 12%, S - 0.01%, V - 0.01, Mo - 1.5%, Ti - 3%, V - 0.001%, Al - 0.6), nickel-based superalloy (Fe - 4%, C - 0.1%, Si - 0.6%, Mn - 0.5%, S - 0.01%, P - 0.01%, Cr - 15%, Ce - 0.01%, Mo - 4%, W - 6%, V - 0.3%, Ti - 2%, Al - 2%, B - 0.01%), the changes in the minimum surface wear, maximum cutting path, and cutting temperature in the processing of these materials, as well as the experimental data analysis showed that the extreme values of changes in the materials’ physical and mechanical properties under the temperature impact can be defined as the minimum surface wear temperature and maximum cutting path temperature, that is, the conditions corresponding to the maximum workability of the materials. It is possible to use the materials physical and mechanical property dependence on temperature for defining the maximum material workability temperature when processing it by cutting. The article suggests a method to define the maximum material workability temperature.

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Section: Introductionmentioning

confidence: 99%

Analysis of Possible Application of Temperature Dependences of Processed Materials’ Physical and Mechanical Properties to Define the Maximum Workability Temperature

Vasilega

Zyryanov

2017

KEM

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“…Maddalena et al applied DFMEA in the feasibility phase of Automotive CMOS Image Sensors development [25]. Klochkov et al assessed the process of can stock production by a detailed PFMEA [26]. Since there are numerous studies, many literature review papers can be encountered in the literature.…”

Section: Failure Mode and Effect Analysis (Fmea)mentioning

confidence: 99%

Machine Vision Supported Quality Control Applications in Rotary Switch Production by Using Both Process FMEA and Design FMEA

KARACAN¹,

ERDOĞAN²,

İĞDİL³

et al. 2021

Natural and Applied Sciences Journal

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Emerging in the past few decades, Industry 4.0 has wide effects over production lines with an increasing number of novel applications. These applications implement more than one of the tools of Industry 4.0. These tools include but are not limited to internet of things (IoT), big data, cloud computing, artificial intelligence, augmented reality, virtual reality, machine to machine communication (M2M), smart robot applications, etc. The aim of these efforts is mainly to acquire smarter manufacturing systems. With spreading Industry 4.0 methodologies, the role of sensors became more important to respond to new demands. One of the most important sensor types in this sense is the camera which now has wide variants in different forms. Applying machine vision algorithms via cameras grants optimization of many critical processes. In this perspective, the quality of both product and process should be handled as a key performance indicator that may be continuously enhanced for excellence. Machine vision algorithms may be adapted to check and manage quality in designated control points on the production lines. This study focuses on the control of the quality of rotary switches that are widely used in household appliances like ovens and washing machines. Rotary switches are critical components of an appliance since they direct the flow of electricity within the product. A failure in the functionality of this component directly causes the failure of the main product. Hence, the quality rate of rotary switches should be calculated in defective parts per million (dppm) units. An intense quality control procedure is required to achieve low dppm rates during production. As a real-life application, a camera system is integrated into the rotary switch production line on a selected point. Classification algorithms are developed on a cost-effective platform to perform visual quality checks of the rotary switches and qualify as "Ok" or "Defective". The selected point ensures a high percent check of quality criteria while enabling repair of the defective parts with minor interventions. This control aims to identify a defective rotary switch as soon as possible since most of the defects are irreversible IDUNAS

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“…However, few studies have verified how these disturbances should be prioritized in a job shop environment. The prioritization of these disturbances is usually performed based on failure mode and effect analysis (FMEA) and lacks linkage with the desired operational outcomes (e.g., service, quality, and cost) [10,11]. Moreover, there are still some deficiencies in visual analysis, effective calculation, and explicit priority of job shop disturbances.…”

Section: Introductionmentioning

confidence: 99%

A Modified FMEA Approach to Predict Job Shop Disturbance

Qiu

Zhang

2022

Processes

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Failure modes and effects analysis (FMEA) is a systematic approach that focuses on evaluating critical disturbances in a system. However, traditional FMEA has its own drawbacks, such as invalid computations and ambiguous priority definitions, which lead to many constraints in the application of complex production processes, especially in job shops with various resources. Therefore, this paper proposes an analytic disturbance prediction method for job shop with multiple resources and multiple evaluation indexes, which combines the vector computing techniques, FMEA, and fuzzy analytic hierarchy process (FAHP). In contrast to other work, this paper focuses on the establishment of FMEA mathematical model to improve the readability of multi-resource disturbance risk results. To this end, the projection of the disturbance vector is visualized to reduce repeated calculation results, triangles and trapezoids are used as membership functions to improve the accuracy of weight, and the differentiation index is used to reduce the ambiguity of priorities. The proposed method can effectively discover the critical disturbances and enable managers to undertake more assertive decisions.

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Development of FMEA Method with the Purpose of Quality Assessment of Can Stock Production

Cited by 28 publications

References 0 publications

Analysis of Possible Application of Temperature Dependences of Processed Materials’ Physical and Mechanical Properties to Define the Maximum Workability Temperature

Analysis of Possible Application of Temperature Dependences of Processed Materials’ Physical and Mechanical Properties to Define the Maximum Workability Temperature

Machine Vision Supported Quality Control Applications in Rotary Switch Production by Using Both Process FMEA and Design FMEA

A Modified FMEA Approach to Predict Job Shop Disturbance

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