Electronic Manufacturing Companies Research Articles

Ipar 4.0 szemléletű tesztelés és validálás kialakításának hatásai az elektronikai gyártásban

The continuous demand increase of electronic items challenges the electronic manufacturing companies. The economic and manufacturing challenges, and the Industry 4.0 based solutions of having a great product portfolio of a regional, original equipment manufacturer are presented in this study. The acquirement and the implementation of the principles of Industry 4.0 results a new production environment, but the positive effects of that can be demonstrated from financial and production efficiency sides. The mindset change of the test and validation area of an electronic company, and the steps required to achieve Industry 4.0 based test solutions are presented in this article. You can read about the practical implementation of a pioneering technology in the field of informatics, Big Data oriented data processing in a real manufacturing environment. The changes related to hardware and software design and data acquisition are presented, also you can read about the resulting cost saving, production efficiency improvement and product output growth of the study.

A hybrid generalized TODIM approach for sustainable 3PRLP selection in electronic manufacturing industry

Under the pressure of globalization, environmental protection/resource consumption, and the intensification of market competition, various industries have recognized the significant importance of sustainable supply chain management (SCM), in which reverse logistics (RL) has attracted many concentrations from governments to enterprises and the public. However, it is relatively difficult to operate RL autonomously for most electronic manufacturing companies whose core businesses and competition advantages are not in logistics operations because of limited resources and professional skills. Therefore, it is a good choice to escape from the predicament by selecting an appropriate third-party reverse logistics provider (3PRLP) with professional skills for outsourcing and accomplishing the RL business. Generally, evaluation and selection of a 3PRLP is regarded as a multi-attribute group decision-making (MAGDM) process, in which four aspects, namely, the evaluation attributes system, weight of experts and attributes, preference information representation and alternative ranking method have impacts on the decision-making results. Therefore, this paper constructs an MAGDM framework named generalized TODIM (TOmada de DecisãoInterativa e Multicritério, Portuguese acronym for Interactive multicriteria decision-making) under a hybrid information environment, which includes crisp numbers, interval numbers and fuzzy linguistic terms, for solving the problem. It provides a useful reference for manufacturing enterprises to find out the optimal 3PRLP from many alternatives. In particular, the use of different information forms for different evaluation attributes can not only facilitate decision makers to provide their judgments, but also effectively retain the original decision information as much as possible. Utilization of the generalized TODIM method is helpful for considering the risk attitudes and psychological preference behaviors of decision-makers. Finally, to demonstrate the feasibility and effectiveness of the proposed method, a case study relates to select a sustainable 3PRLP in an electronic manufacturing company was conducted. The findings show that the company should pay more attention to the attributes related to social responsibility, service quality and cost when selecting alternative 3PRLP under the sustainable SCM environment. It also provides useful suggestions for 3PRLP themselves to improve their competitiveness from these aspects. Moreover, the sensitivity and comparative analysis demonstrated the necessity and superiorities of comprehensively considering weights of experts and attributes, adopting hybrid information formats, and taking into account the risk attitudes and psychological preference behaviors of decision-makers during the evaluation and selection process.

Study on the Optimization of the Material Distribution Path in an Electronic Assembly Manufacturing Company Workshop Based on a Genetic Algorithm Considering Carbon Emissions

In order to solve the problems of high carbon emissions, low distribution efficiency and high costs related to the process of material distribution in manufacturing workshops, a multi-objective workshop material distribution path optimization problem model is established, and the model is solved using an improved genetic algorithm. The problem is processed using Gray code and crossover and variation operations with a genetic algorithm. To improve the search accuracy and convergence speed of the algorithm, an adaptive mutation method is proposed to enhance the diversity of the population and to achieve global optimal path objective finding. The improved algorithm is applied to workshop path multi-station logistics path planning, which effectively solves the transport path optimization and station solving problems in workshop logistics distribution, and the convergence speed and convergence accuracy of the algorithm are significantly improved. Finally, a simulation analysis is carried out on the optimization of the production material distribution of a smart gas meter workshop owned by K Company, which is an electronic assembly manufacturing company. We used MATLAB software for the case company logistics distribution route model for data analysis and solving. Due to the consideration of carbon emissions, we did not consider two kinds of experiments, which were two different cases of the optimal path. The experimental results verify that the distribution optimization scheduling model can meet the demands for immediate material distribution in the production workshop, which is conducive to improving material distribution efficiency, reducing logistics costs and achieving the goal of lowering carbon emissions. This optimization model has a certain utility in that in the current context of aiming for carbon neutral and carbon peaking, early low carbon distribution layout can reduce the environmental cost of the enterprise, making material distribution a more environmental economic path.

Angel or devil? a study of the threshold effect of patent strategy on the relationship between patent thicket and corporate market value

ABSTRACT Patent strategies are an effective means of mitigating the negative effects of patent thickets on corporate market value. In reality, however, inappropriate patent strategies tend to exacerbate the negative effects of patent thickets. In this study, we used 2009–2019 panel data of 419 Chinese electronic equipment manufacturing companies, applied a panel threshold model, and analysed the influence mechanism. We empirically investigated the boundary dividing patent application, patent withdrawal, patent portfolio, and patent maintenance strategies from ‘angel’ to ‘devil’ and the influence mechanism of patent thickets on corporate market value. This study arrives at several conclusions. (i) Patent thickets exert a negative effect on corporate market value. (ii) Patent application and withdrawal strategies play a fully mediating role in the negative effect of patent thickets on corporate market value, while patent portfolio and maintenance strategies play a partially mediating role. (iii) Patent application, withdrawal, and maintenance strategies exhibit a double threshold effect, while patent portfolio plays a single threshold role. This study enriches the research on patent thickets.

CORRELATION BETWEEN LIFE SATISFACTION AND HEART RATE VARIABILITY COHERENCE AMONG BLUE-COLLAR WORKERS – CASE STUDY IN A MALAYSIAN ELECTRONIC MANUFACTURING COMPANY

Introduction. In addition to having a higher risk of more physical and psychological health problems, blue-collar workers form the largest proportion of the workforce in industries. Thus, it is important to ensure their well-being which can have broader benefits for economic growth and society. This study aims at investigating the relationship between subjective well-being, namely life satisfaction and heart rate variability (HRV) coherence as an objective indicator. The second aim is to evaluate whether any differences in HRV coherence across three levels of life satisfaction groups (dissatisfied, neutral, and satisfied) after a brief session of resonant breathing training. Methods. A total of 313 female blue-collar workers from an electronic manufacturing company participated in this study. All participants completed a satisfaction with life scale (SWLS). Their HRV coherences were then recorded at baseline or rest and after attending a brief session of resonant breathing. Results and Analysis. We found a significant correlation between life satisfaction and HRV coherence after the intervention but not at rest, implying a current state of cardiac activity did not reflect workers’ attitudes toward their life. Moreover, less satisfied workers showed greater cardiac coherence improvement than those who perceived more satisfaction in life. Discussion. This finding suggests that brief resonant breathing training can help workers achieve greater HRV coherence which offers its potential as a strategy to combat workplace stressors.

A Novel System to Increase Yield of Manufacturing Test of an RF Transceiver through Application of Machine Learning

Electronic manufacturing and design companies maintain test sites for a range of products. These products are designed according to the end-user requirements. The end user requirement, then, determines which of the proof of design and manufacturing tests are needed. Test sites are designed to carry out two things, i.e., proof of design and manufacturing tests. The team responsible for designing test sites considers several parameters like deployment cost, test time, test coverage, etc. In this study, an automated test site using a supervised machine learning algorithm for testing an ultra-high frequency (UHF) transceiver is presented. The test site is designed in three steps. Firstly, an initial manual test site is designed. Secondly, the manual design is upgraded into a fully automated test site. And finally supervised machine learning is applied to the automated design to further enhance the capability. The manual test site setup is required to streamline the test sequence and validate the control and measurements taken from the test equipment and unit under test (UUT) performance. The manual test results showed a high test time, and some inconsistencies were observed when the test operator was required to change component values to tune the UUT. There was also a sudden increase in the UUT quantities and so, to cater for this, the test site is upgraded to an automated test site while the issue of inconsistencies is resolved through the application of machine learning. The automated test site significantly reduced test time per UUT. To support the test operator in selecting the correct component value the first time, a supervised machine learning algorithm is applied. The results show an overall improvement in terms of reduced test time, increased consistency, and improved quality through automation and machine learning.

Occupational Safety and Health Risk Assessment in an Electronic Manufacturing Company in Indonesia

The health and safety team at Sharp Electronics Indonesia Ltd identified two departments that urgently needed evaluation: Cabinet PU B Department and Total PU B Department, as they have the highest potential for accidents. Based on historical data from work accident reports from the Refrigerator Division between 2015 and the beginning of January 2020, two departments had a tendency to experience work accidents annually: the Door PU A Department and the Roll Forming B Department. The objective was to identify potential hazards in the production process, assess the risk that arises from the production process, and provide risk control recommendations for each department in the Refrigerator Division. The HIRARC approach was used to identify potential dangers by linking potential hazards between workers, tasks, work equipment, and the work environment in an orderly manner. Hazards were identified using the JSA method. Risk assessment was conducted using a semi-quantitative analysis, and risk control was done using a risk control hierarchy. Based on the risk assessment, the risks that needed to be addressed through risk control were head injury, being hit by a cabinet, decreased hearing function, lower back pain, being hit by a compressor, and having a hand clamped by a conveyor. The identification and assessment of occupational accident risks in the four departments revealed six potential occupational accident risks. The highest risk value was head injury and being hit by a cabinet, which were in the very high category in the Cabinet PU B and Total PU B departments.

A Fuzzy Analysis Approach to Green-Resilient Supplier Selection in Electronic Manufacturing Systems

Adopting environmentally sound practices and utilizing resilient issues to face disruptive events and risks are new important agendas for enterprises, governments, and societies. The issue of supplier selection and evaluation in accordance with green and resilient principles has received little attention in the electronic industry. So, the present study aims to consider both criteria of resilience and greenness in a new supplier selection model. This study presents an integrated decision-making method based on the fuzzy set theory and data envelopment analysis (DEA) approach for supplier selection in a supply chain network in an electronic manufacturing company. The fuzzy set theory was used for analyzing suppliers' indicator weights, the suppliers' performance, and rating them with respect to subcriteria. Then, the obtained data were aggregated to classify and prepare them for use in a version assurance region of the DEA method with one dummy input and three output variables to rank the suppliers. The performance of the proposed DEA-based model has been verified through the sensitivity analysis and it has been validated by the existing FIS-based model in the literature. Furthermore, the proposed DEA-based model can be designed with any number of suppliers and criteria and subcriteria.

Antecedents of kaizen culture and its effect on operational performance: perspective of manufacturing companies in Malaysia

PurposeThe purpose of this research is to examine the effect of kaizen culture on innovation and operational performance of electrical and electronic manufacturing companies in Malaysia. A research framework, with underpinning theories of dynamic capabilities and socio-technical systems, was conceptualized to investigate the interplay of these relationships.Design/methodology/approachData were collected from 123 manufacturing companies using an online survey and analyzed with IBM SPSS Statistics version 24.0 and the partial least squares structural equation modeling (PLS-SEM) (SmartPLS) version 3.2.8.FindingsUltimately, the findings proved that kaizen culture is crucial for organizations to optimize their operational performance and can be nurtured through the implementation of process innovation and organizational innovation.Originality/valueUnlike past studies, this research examines the concepts of innovation, kaizen culture and operational performance in a single study; thus, provides further opportunities for new discoveries through such relationships. Also, the novelty is identifying that kaizen culture can be nurtured via innovation.

Redesigning production floor layout with process layout and product layout approach in an electronic appliance manufacturing company

The system of material handling is less systematic becomes a big problem and disrupts the smoothness of the production process that affects the system as a whole. Problems that occur in the company is a workstation that is too dense so that the trajectory of material handling (forklift) becomes narrow, in addition, there are also work stations that are located too far, causing empty space in the production floor area. This long-distance resulted in a great displacement moment that affected the amount of material handling cost. Therefore, it’s important to redesigning the facility layout to reduce material handling cost at the company. The goal of this research is to get an optimal design of facilities layout that provides minimal displacement moment by comparing the initial layout with the proposed layout with Process Layout and Product Layout approach. Process Layout is designed using graph theory while the product layout is designed using the method of Systematic Layout Planning. After that, the layout of the production floor with the product layout approach improves material handling efficiency with the displacement moment of the proposed production floor layout is 36.160 meters per year or 19.4% lower than the actual layout.

A Novel Process to Setup Electronic Products Test Sites Based on Figure of Merit and Machine Learning

Consumer electronic manufacturing (CEM) companies maintain a range of electronic products that are designed and tested according to the type and end-user requirements. These electronic products go through a validation and verification test for proof of design and a manufacturing test for checking reliability, quality, and manufacturing defects. Testing is carried out using test sites, designed based on the electronic product type. Currently, there is no standard approach for setting up a test site for electronic products. In this research, two processes are presented, for setting up new test sites and optimization of existing test sites for consumer and other electronic products. The proposed processes include a voice of customer (VoC) interface, that is based on a unique dataset and through machine-learning technique automatically translate customer information into customer requirements, and a figure of merit (FoM) presented as an outcome of this research using several key test-related parameters. These proposed processes are an important step towards defining a standard approach for setting test sites for consumer and other electronic products. The processes are implemented using a software application developed in LabVIEW, which is linked to a database containing test data for around 400 products collected as part of this research and form a knowledge base for the proposed processes. Finally, the processes are validated by setting up a new experimental test site for an RF receiver and optimization of an existing test site of an antenna system.

Partner selection in sustainable supply chains: A fuzzy ensemble learning model

With the increasing demands on businesses to operate more sustainably, firms must ensure that the performance of their whole supply chain in sustainability is optimized. Because partner selection is critical to supply chain management, focal firms now need to select supply chains partners that can offer a high level of competence in sustainability. This paper proposes a novel multi-partner classification model for the partner qualification and classification process, combining ensemble learning technology and fuzzy set theory. The proposed model enables potential partners to be classified into one of four categories (strategic partner, preference partner, leverage partner and routine partner), thereby allowing distinctive partner management strategies to be applied for each category. The model provides for the simultaneous optimization of both efficiency in its use of multi-partner and multi-dimension evaluation data, and effectiveness in dealing with the vagueness and uncertainty of linguistic commentary data, in the partner evaluation process. Compared to more conventional methods, the proposed model has the advantage of offering a simple classification and a stable prediction performance. The practical efficacy of the model is illustrated by an application in a listed electronic equipment and instrument manufacturing company based in southeastern China.

An Empirical Study on the Supply Chain Management Capacity and Financial Performance of Electronic Manufacturing Companies in Korea

An Empirical Study on the Supply Chain Management Capacity and Financial Performance of Electronic Manufacturing Companies in Korea

Pengembangan Model Pengukuran Kesiapan Industri 4.0 Untuk Perusahaan Manufaktur di Indonesia

Nowadays, manufacturing companies in Indonesia are facing a great challenge in Industry 4.0 era. Manufacturing companies perceive Industry 4.0 is complex and could disturb their business process with uncertainty in results by implementing it. In other side, manufacturing companies also have difficulty in assessing their readiness to start Industry 4.0 transformation process and fail to prepare strategies and action plans clearly. This research developed a measurement model of Industry 4.0 readiness with 2 aspects, 5 dimensions and 20 variables that could be used by manufacturing companies to asses their current state. The dimensions “Awareness” and “Leadership and Strategy” are used to measure company readiness in “Knowledge” aspect, while the dimensions “People and Culture”, “Technology” and “Operation” are used to measure company readiness in “Resources Capability” aspect. The result of the measurement categories the company in 4 level of readiness, i.e.: “Not Ready”, “Conditional Ready”, “Basic Readiness” and “Fully Ready”. This model has been tested and used to measure Industry 4.0 readiness for an electronic manufacturing company located in Jabodetabek and showed that the model is easy and practical to be used in a real manufacturing company. Keywords: Industry 4.0, readiness measurement, readiness model, readiness index

The effects of overproduction on future firm performance and inventory write‐downs

AbstractThis study aims to examine the effects of current overproduction on future operating efficiency and inventory write‐downs. Using electronic manufacturing companies listed on NYSE/AMEX/NASDAQ during the period of 2003–2013, this study: (i) employs the interaction term between relative fixed cost levels and excess quantity of inventory produced to measure overproduction, (ii) utilizes the dynamic slacks based measure model to estimate operating efficiency, and (iii) examines inventory write‐downs. Our findings show that overproducing firms experience improved but unsustainable subsequent operating efficiency, as overproduction is a result of optimistic sales forecasting, which leads to higher subsequent inventory write‐downs. Overall, this paper suggests that production managers should be prudent in anticipating future sales demand, as short product life cycle might cause higher inventory obsolescence on excess production.

Simulation of mixed-load testing process in an electronic manufacturing company

The automatic testing machine, called by mixed-load tester, has ability to load and test multiple product families in different testing durations simultaneously. However, the high product mixes for each product family undergoes a different process flow. In addition, the capability of the robot inside tester used for loading and unloading a product to each slot makes the capacity planning problem more complicated. It effects low tester utilization. This paper developed simulation models of capacity planning scenarios under demand and testing time uncertainty. These scenarios are built by robust optimization to handle worst case condition. The result shows the proposed solutions gives better tester utilization and improves the decision making process by providing more detailed and precise information about capacity planning under uncertainties that was not available in company`s current method. To the best of our knowledge, this developed model is the first one considering the mixed–load tester under uncertainties.

Anatomy Of An Acquisition: The Challenges Of Selling A Privately Held Electronics Manufacturing Company

Sweeny Electronics is a family-owned S Corporation based in St. Paul, Minnesota. The company was started in 1946 by a returning army veteran, Frank Sweeney, and focused on the heating, air quality and cooling markets. The company has survived numerous recessions, market consolidations, and manufacturing challenges. The company is currently run by the third generation of the Sweeney family, George Sweeney, who is the current owner and CEO, is approaching retirement age. The board of directors has seven members: George Sweeney, his wife Jane and five members of the business community. Under the direction of the CEO, the board has determined that there is no “heir apparent” in the family or in the current management team. They have elected to hire an investment banking firm to position the company for an asset-based sale. Sweeney would like to sell the company for estate planning purposes and allow him to transition to a consulting role with the new owner.

Occupational Health Risk Assessment in the Electronics Industry in China Based on the Occupational Classification Method and EPA Model.

The awareness of occupational health risk management in the electronics industry is weak in China, and many Chinese occupational health management regulations have not been effectively implemented. China’s current occupational hazards classification method and the Environmental Protection Agency (EPA) inhalation risk assessment model recognized internationally were used to perform health risk assessments for a chip manufacturing company in the electronics industry in order to determine the existing problems and put forward the optimization proposals of the occupational hazards classification method in China. The results showed that the detected concentrations of toxic and harmful chemicals in all testing points did not exceed the occupational health exposure limits in China. According to the EPA inhalation risk assessment model, the highest values of non-carcinogenic risks of ammonia, chlorine, fluoride, sulfuric acid, hydrogen chloride, ethylene glycol, phosphine, boron trifluoride, isopropanol, benzene, and xylene were 5.10, 67.12, 1.71, 45.98, 1.83, 1.43, 160.35, 46.56, 2.52, 5.55, and 5.37, respectively, which means workers in electronic chip manufacturing companies exposed to these chemicals have higher occupational health risks. However, on the basis of the occupational hazards classification method, the occupational health risks of exposure to the toxic and hazardous chemicals are relatively harmless operations. The evaluation results of the EPA inhalation risk assessment model are generally higher than those of the occupational hazards classification method. It’s recommended to refine the value of occupational exposure limit B, taking more characteristics of the hazard factors into account and fuzzifying the parameters to optimize the occupational hazards classification method. At the same time, it is suggested that the electronic chip manufacturing company should conduct anti-virus risk management covering in three aspects: increasing the awareness of occupational hazards, enhancing system ventilation, and improving personal health management measures.

Perception on Prolonged Standing Work in Electronic Manufacturing Company

Prolonged standing is one of the common activities in electronic industry as the task requirement. Prolonged standing can cause discomfort on the body of the workers and can lead to injury and occupational disease. The purpose of this study is to investigate standing workers perception on the fatigue and the discomfort on their respective body region for 12 hours working time. The subjects are the 80 workers with a good health condition and at least 6 months tenure. The subject data are collected via questionnaires and Likert scale to define the discomfort, pain, and fatigue. The workers were interviewed regarding their job and perceived fatigue discomfort. The results show the domination of the lower body region with the higher mean at the lower back, legs, and foot ankle. No statistically significant differences were found between the job tenure and body part discomfort pain and fatigue. There is a significant relation between gender and discomfort pain on legs and foot ankle. The result also shows a strong relation between age and the discomfort body parts of thigh and foot ankle. The perceptions of the workers towards discomfort pain and fatigue cause by prolonged standing during performing the task. The results from this study will provide a view for industrial consultants or ergonomist with evidence to support for ergonomic interventions for prolonged standing activity such as job rotation and work-rest schedule.

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