The objective of this study is to identify the priority of elements for effective implementation of MES in small and medium-sized manufacturing enterprises trying to develop into smart factories. For this purpose, the Delphi method and the Analytic Hierarchy Process(AHP) mothod are applied. As a result of the study, the cooperation of the members in the supply chain is the most important factor for small and medium-sized enterprises in order to survive in the global competitive environment. Therefore, the enterprises need to make various efforts to create synergies through the technical strength of suppliers and the cooperation in the process of introducing and operating MES.

Recently, as ESG management has become an important issue, major companies in the automotive parts manufacturing industry are conducting ESG evaluations of their suppliers for the purpose of supply chain management. The results of these evaluations are being incorporated into contractual agreements. However, many small and medium-sized enterprises(SMEs) are lacking in their capacity and resources to effectively respond to ESG evaluations. Furthermore, existing ESG management guidelines do not provide an industry-specific guidance, making it necessary to establish industry-specific guidelines that SMEs can refer to. Therefore, in this study, the evaluation Indicators of ESG supply chain assessments are surveyed, which is conducted by domestic major automotive parts companies and global automobile manufacturers. Then 56 supply chain ESG evaluation Indicators are derived. Also, ESG management indicators for SMEs is analyzed through the Importance-Performance Analysis(IPA), based on an interview of expert groups. Therefore, this study could propose industry-specific ESG guidelines, based on the results of the derived indicators, which reflects the need for SMEs to practice ESG management within certain boundaries.

This study is to develop a diagnostic model for the effective introduction of smart factories in the manufacturing industry, to diagnose SMEs that have difficulties in building their own smart factory compared to large enterprise, to identify the current level and to present directions for implementation. IT, AT, and OT experts diagnosed 18 SMEs using the "Smart Factory Capacity Diagnosis Tool" developed for smart factory level assessment of companies. They analyzed the results and assessed the level by smart factory diagnosis categories. Companies' smart factory diagnostic mean score is 322 out of 1000 points, between 1 level (check) and 2 level (monitoring). According to diagnosis category, Factory Field Basic, R&D, Production/Logistics/Quality Control, Supply Chain Management and Reference Information Standardization are high but Strategy, Facility Automation, Equipment Control, Data/Information System and Effect Analysis are low. There was little difference in smart factory level depending on whether IT system was built or not. Also, Companies with large sales amount were not necessarily advantageous to smart factories. This study will help SMEs who are interested in smart factory. In order to build smart factory, it is necessary to analyze the market trends, SW/ICT and establish a smart factory strategy suitable for the company considering the characteristics of industry and business environment.

Smart Manufacturing Factory is a paradigm of the future lead to the fourth industrial revolution that led Germany and the United States. Now the automation of the production facility and won a certain degree, and through the process of integrating the entire process, including planning, design, distribution of information and communication technology products in emerging as a core competitiveness of the national economy. In particular, the company accelerated the smart factory building in order to improve the manufacturing industry, cost savings and productivity simply to incorporate internet of things(IoT),Robot, artificial intelligence, big data technology as a factory automation level of sophistication of the system and out to progress to the level that replaces human labor have. In this we should look at the trend of promoting domestic and foreign factories want to present these smart strategies for Korea.

This research examines the causal relationships between supervisor trust and organizational citizenship behavior(OCB) and the mediating role of organizational trust on OCB. Using the sample of 282 small and medium sized enterprises’ employees, this study analyzes three alternative hypotheses centered around supervisor trust, organizational trust, and OCB. The results show that supervisor trust has a strong positive effect on OCB. Second, organizational trust is positively related to OCB. Third, this research proves that partial mediating effects of organizational trust exist between supervisor trust(relational trust) and OCB(civic virtue, sportsmanship). Finally, this research proves that a full mediating effect of organizational trust exists between supervisor trust(calculative trust) and OCB(sportsmanship). This study recommends supervisor trust, organizational trust be valued in order to increase OCB vital for organizational effectiveness or productivity in small-medium sized manufacturing enterprises.

OSHMS(Occupational Safety and Health Management System) is able to define as a typical convergence of all kinds of activities and elements that support maintaining safety at workplace and protecting employee's health. In particular, fundamental function of OSHMS is preventing diverse hazards at workplace through high level of regulation compliance. Furthermore, insuring safety in workplace, protecting employee's health and increasing effectiveness in manufacture are OSHMS's additional functions. Based on the division of manufacture in 2009 Survey on Current Status of Occupational Health & Safety data, the study analyses certain relation between OSHMS and level of regulation compliance. The main finding is that most activities and elements which formed by OSHMS are being affected by regulation clauses.

  Manufacturing Execution System (MES) is a system that companies can use to measure and control critical production activities. This paper shows case study of implementation of MES (Manufacturing Execution System) and its methodology in a medium sized pr

The study aims to identify and measure factors affecting the salaries of employees in manufacturing enterprises in Hanoi, the important area of Vietnam’s economy. We conducted a questionnaire consisting of 31 observation variables with a 5-point Likert scale. Independent variables were measured from 1 “without effect” to 5 “strongly”. Based on the literature review and results of interviews, a total of 350 questionnaires were sent to participants; 300 of them met the standards and were subject to be analyzed. The results of Exploratory Factor Analysis (EFA) and Multiple Regression Analysis (MRA) identify six main determinants influencing the salaries of employees in manufacturing enterprises in Hanoi, including Paying views of business leaders (PV), Financial ability of the enterprise (FA), Capacity of workers (CW), Capacity of the contingent of employees engaged in salary work (CC), Role of grassroots trade unions (TU), and State policies and laws on labor – salaries (STL). Based on the findings, some recommendations have been proposed to help the firm leaders design appropriate personnel policies for creating better job satisfactions for employees in the future. On this basis, the authors propose a number of recommendations to improve the salaries of employees in manufacturing enterprises in Hanoi.