Assessment and Prioritize Risk Factors of Financial Measurement of Management Control System for Production Companies Using a Hybrid Z-SWARA and Z-WASPAS with FMEA Method: A Meta-Analysis

The management control system in an industry is managerial, directional, hindrance, and cohesive action in order to cohere and regulate various branches and sub-branches. In fact, it is a system that supports the real state of matters in the right way. This method is intended at assuring that the purposes and activities carried out have the desired outcomes and eventually lead to the objects and purposes of the company. In this matter, the financial and non-financial management control system is essential both when it comes to strategy community; Consequently, in this paper, the management control system is classified into financial and non-financial categories because such analysis gives a chance to get a broad assessment of a management control system relationship in organizations. In this paper, we evaluate the relationship between business strategy and management control system and their influences on financial performance measurement of a manufacturer (a case study of Maral co.) with the use of Merchant’s theory. Furthermore, In this case, a decision-making strategy centered on the FMEA is used to identify and prioritize risk factors financial of the control system in companies. Nevertheless, because this strategy has some significant limitations, this research has presented a decision-making approach depending on Z-number theory. For tackle, some of the RPN score’s drawbacks, the suggested decision-making methodology combines the Z-SWARA and Z-WASPAS techniques with the FMEA method. The findings reveal that in the non-financial management control system element, customer satisfaction, and in the financial component, cost standards are at the largest level of weight. Furthermore, the strategic planning factor with a rate of 2.95 and the deviation analysis factor with a rate of 2.87 is at the lowest level, respectively. In sum, market or industry changes are the primary cause of risk in businesses, according to FMEA methodology and the opinions of three professionals.

RISK ASSESSMENT IN 13-STORY BUILDING PROJECTS WITH THE FAILURE MODE AND EFFECT ANALYSIS (FMEA) METHOD AND THE DOMINO EFFECT

The building construction project is one of the activities that can pose a safety risk. Work safety risk assessment can be done using the Failure Mode and Effect Analysis (FMEA) method and looking at the Risk Priority Number (RPN) value. The purpose of this research is to take a case study of the building Office in determining the highest RPN and provide recommendations on its management. This project consists of 13 earthworks, passenger hoist, tower crane, scaffolding jobs, ironworks, formwork work, foundry work, mechanical, electrical plumbing (MEP) work, welding work, and floor wall doing works, and ceramic installation work. The highest RPN from the observations occurred in Iron Fabrication which can cause fingers hit by a bar cutter and bender. In this case, personal protective equipment (PPE) is significant in preventing these impacts from occurring in the project work area.

Modified Failure Mode and Effect Analysis Approaching to Improve Organization Performance based on Baldrige Criteria- A Case Study of AN Electro-medic Industry

Full attention is paid to quality in manufacturing; however, less effort is made to develop the organizational performance, which drives overall manufacturing quality. This research measures performance of one manufacturing company that in 2020 experienced surging in demand and experiencing barriers to social activities due to the pandemic. The evaluation was carried out using seven variables from the Malcolm Baldrige Criteria for Performance Excellence (MBCfPE) which were elaborated into 43 indicators of organizational performance. Weaknesses and strengths of organizational performance were sharpened through focus group discussions with experts and ended with a performance improvement solution with a priority rank based on risk priority numbers (RPN) of the FMEA method. The highest RPN is 567 and 432, respectively, for national standard implementation in a particular product and operational scheme during emergency conditions like the Cov-19 pandemic. This study contributes to Indonesian research that combines questionnaires and FMEA improvement analysis based on the US Baldrige criterion.

Problems of sustainable “green” development of alternative energy

The paper analyzes the known risks of power supply failure in the case of further development of renewable energy sources. The use of FMEA analysis allowed to analyze the significance of various risks of alternative energy. It is shown that the use of the FMEA method is becoming one of the most important areas of technosphere safety for the further development of alternative energy. The introduction of the share of alternative energy into the total energy balance leads to a decrease in the share of traditional sources of energy generation. In turn, a decrease in the share of traditional sources of energy production in the case of a combination of unfavorable natural factors causes to the collapse of the energy supply system and causes a complete shutdown of alternative energy.

A Proposed Framework for Developing FMEA Method Using Pythagorean Fuzzy CODAS

The purpose of this research article is to develop a hybridization between the Failure Mode and Effect Analysis (FMEA) method and the Combinative Distance-Based Assessment (CODAS) method under Pythagorean Fuzzy environment. The traditional FMEA procedure is based on the multiplication between the parameters of severity, occurrence, and detectability where everyone has equal relative importance; therefore, different combinations of these parameters can generate the same result creating uncertainty in the analysis. In this mode, the hybridization proposed in this research deal with relative importance of each parameter; in the fact to have a more suitable combination which consider the level of knowledge of the experts in the assessment. Finally, a numerical case was carried out concerning the public transportation service to validate our proposal; the results show that 31 failure modes and potential risks can be evaluated using user perceptions, a dominant with high level of knowledge about the public transportation service and an apprentice or common user, as team of experts and exploiting the subjectivity of the information in a mathematical model. Also, we compare the results with a variation of the proposed model with the multi-criteria method multi-objective optimization method by relationship analysis (MOORA); it was observed that the convergence of the failure modes depends on the nature of the mathematical model even under the same conditions at the start.

Failure Mode and Effect Analysis for a military nose landing gear project

Failure Mode and Effect Analysis (FMEA) techniques were originally developed by the US Military and have been used as techniques for assessing the reliability and effects of equipment failures. However, the first notable applications of FMEA techniques are related to the impressive development of the aerospace industry in the mid-1960s. FMEA is a methodology for systematically analyzing the failure modes of a project, product or process, prioritizing their importance, identifying system failure mechanisms, analyzing potential failure modes and the effects of these failures, followed by corrective actions, which are applied in the stage of conceptual and detailed design of the product. All approaches to FMEA methods in the scientific literature converge to achieve three goals, namely: the ability to predict the type of failure that may occur, the ability to predict the effects of the failure on system operation, and the establishment of the steps to prevent failure and its effects on the system operation. The FMEA for the project of a nose landing gear analyzes the failure modes of the product and their effects in operation, as a consequence of project deficiencies and identifies or confirms critical functions. To apply the FMEA method to the project of the nose landing gear of a military training aircraft, the following steps need to be accomplished: product description and identification of components; identification of functions; identification of potential ways of failure; estimating the frequency of causes of failure; appreciation of the severity of effects; assessment of difficulties in detecting defects; calculation of the Risk Priority Number (RPN); establishing the measures and corrective actions for the analyzed project.

Reliability Analysis of Intelligent Manufacturing Systems Based on Improved FMEA Combined With Machine Learning

Along with the booming of intelligent manufacturing, the reliability management of intelligent manufacturing systems appears increasingly important. Failure mode and effects analysis (FMEA) is a prospective reliability management instrument extensively utilized to manage failure modes of systems, products, processes, and services in various industries. However, the conventional FMEA method has been criticized for its inherent limitations. Therefore, this paper devises a method based on improved FMEA model combined with machine learning for complex systems and applies it to the reliability management of intelligent manufacturing systems. The structured network of failure modes is constructed based on the knowledge graph for the intelligent manufacturing systems. The grey relation analysis (GRA) is applied to determine the risk prioritization of failure modes, hereafter the clustering analysis is employed to extract the features of failure modes. The results show that the proposed method can more accurately reflect the coupling relationship between the failure modes compared with the conventional FMEA method. This research provides significant support for the reliability and risk management of complex systems such as intelligent manufacturing systems.

Practical Application of the New Approach To FMEA Method according to AIAG and VDA Reference Manual

System requirements in the automotive industry are constantly evolving and being improved. Currently, the entire supply chain, related to the automotive industry, is subject to the fourth amendment to the technical automotive standard - IATF 16949: 2016 Quality management systems - Detailed requirements for the use of ISO 9001: 2015 in serial production and production of spare parts in the automotive industry. In IATF standard, there are advices called reference manuals that provide important guidance on the quality system in this industry - one of them is the FMEA manual. The new guidelines in this regard, developed jointly by AIAG and VDA, entered into force in June 2019. Presentation of the most important changes introduced, as well as presentation of a practical example of the conducted analysis is the purpose of the article.