• Journal of the Korean Society for Precision Engineering
• /
• v.23 no.2 s.179
• /
• pp.199-206
• /
• 2006

Automatic grease lubricator is equipment that provides adequate amount of fresh grease constantly to the shaft and the bearings of machines. It minimizes the friction heat and reduces the friction loss of machines to the least. This research is to develop automatic grease lubricator by gear driven mechanism with controlled operation time. The ultimate design of this equipment is to lubricate an adequate amount of grease by a simple switch clicking according to the advanced set cycle. The backlash of the gear was minimized to increase the output power. To increase the power of gear mechanism, the binding frequency and the thickness of the coil were changed. To control the rotating cycles of the main shaft according to its set numbers, different resistance and chips were used to design the circuit to controls electrical signals with pulse. The body of the lubricator was analyzed by stress analysis with different constructed angle. The stress analysis for differing loading pressures applied to the exterior body of grease lubricator due to the setup angle, was found that the maximum stress was distributed over the outlet part where the grease lubricator suddenly narrowed contracts. Digital mock-up was analyzed and the rapid prototyping(RP) trial products were tested with PCB circuit and grease. The evaluation of the outlet capacity for RP trial products was conducted, because the friction caused by the outlet on the wall surface was an important factor in the operation of the equipment. Finally, the finishing process was applied to decrease the roughness of the surface to a comparable level and was able to test the performance examination for the product.

• Journal of Construction Engineering and Project Management
• /
• v.10 no.1
• /
• pp.16-32
• /
• 2020

Cost and time control of projects is important in preventing project failure. However, achieving effective cost and time control in practice is often challenging. The challenges of project cost and time control in practice are investigated by carrying out a questionnaire survey on the top 150 construction contractors in the UK followed by in-depth semi-structured interviews of practitioners from 15 construction companies in the country. Quantitative analysis reveals that design change is the most important factor inhibiting the ability of UK contractors from effectively controlling both the cost and time of construction projects. Four of the top five factors inhibiting effective cost control are also the top factors inhibiting effective time control albeit in a different order. These top factors-design changes, inaccurate evaluation of project time/duration, risk and uncertainty, non-performance of subcontractors and nominated suppliers were also found to be endogenous factors to the project. Additionally, qualitative analysis of the interviews reveals 16 key challenges to prevent for effective project cost and time control in practice. These are classified into four categorised based on where they stem from as follows; from the organisation (1. Lack of integration of cost and time during project control, 2. lack of management buy-in, 3. complicated project control systems and processes, 4. lack of a project control training regime); from the construction management/project management approach (5. Lapses in integration of interfaces, 6. project control not being implemented from the early stages of a project, 7. inefficient utilisation and control of labour, 8. limited time devoted to planning how a project will be controlled at the outset); from the client; (9. Excessive authorisation gates, 10. use of adversarial and non-collaborative forms of contracts, 11. communication problems within client set-up, 12. obstructive client representatives) and; from the project team (13. Lack of detailed/complete design, 14. lack of trust among the project partners, 15. limited time devoted to project control on site, 16. non-factual reporting). The study posits that knowledge of these project control inhibiting factors and challenges is the first step at ensuring they are avoided and enable the implementation of a more effective project cost and time control process in practice.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.1
• /
• pp.417-425
• /
• 2020

In this paper, value relevance of the level of dependence on separate accounts in non-life-insurance companies is studied. As noted by Shim et al. (2015), the separate accounts of insurance companies consist of contracts with different attributes from the general accounts, so it is likely that firm value will vary depending on the insurer's dependence on the separate accounts. Thus, in this paper, an empirical analysis has been conducted using quarterly financial data and stock price data from domestic listed non-life-insurance companies from 2011 to 2018. The analysis shows that variables representing the level of dependence on separate accounts have a significant negative relevance to firm value. These results may suggest that changes in the proportion of a non-life-insurer's separate accounts may result in a change to its firm value under the same net assets and net income scales in aggregate accounts. This study provides management implications for the operation of separate accounts from the perspective of maximizing firm value. In addition, this study suggests that disclosure system improvement would be necessary to more directly report the operational performance of the separate accounts.

• Journal of Arbitration Studies
• /
• v.29 no.3
• /
• pp.39-52
• /
• 2019

There are various factors to consider when parties to an international agreement draft a dispute resolution clause in their written contract. These factors can be classified into two categories. The first category is about the parties and the nature of the contract, such as the parties' places of business and whether the contract contains a simple transaction or has a complicated nature. The second category is about the applicable rules of the parties' places of business or performance such as the private international law, service of process rules, and enforcement of court judgment and arbitration award rules. When parties to an international contract agree to a litigation, they normally choose a forum court and a governing law. In selecting a forum court and a governing law, the parties must consider private international law, service of process rules, and enforcement of judgement rules of candidate forums. In case the parties agree to an arbitration, they have to choose between institutional arbitration and ad hoc arbitration. For ad hoc arbitration, parties still need to further agree on which arbitration rules to use, and in which place the arbitration shall take place. Mediation involves a similar kind of decision as with arbitration. Traditionally, national courts of the parties' places of business have been used as litigation forums in dispute resolution clauses but, recently, arbitration is being increasingly employed as an alternative dispute resolution method in international contracts. Moreover, there have been international efforts to utilize mediation as a dispute resolution method in international commercial issues. Rather than simply taking a dispute resolution clause provided in a sample written contract, parties to an international contract must carefully consider various relevant factors in order to insert a dispute resolution clause which will work well for a particular contract.

• Journal of Convergence for Information Technology
• /
• v.11 no.12
• /
• pp.127-137
• /
• 2021

The purpose of this study was to suggest the justification for social recognition of childcare staff through a review of Axel Honneth's recognition theory of childcare staff's caring work, the Constitution, the Infant Care Act, and the National Human Rights Commission Act. As a result of the study, first, the poor working environment of childcare staff was confirmed. Despite the continuous intervention of childcare policies to improve the working environment of childcare teachers, poor working conditions such as annual/monthly vacation and rest time guarantee were confirmed. Second, the human rights violations of childcare staff were confirmed. The installation of CCTV installed to prevent child abuse in childcare institutions confirmed not only the human rights violations of childcare staff but also the psychological pressure of childcare staff who are monitored 24 hours a day. Third, this study has significance in that it suggests the justification for social recognition of childcare staff through revision and supplementation of the current law for appropriate performance evaluation of childcare.

• International Area Studies Review
• /
• v.14 no.3
• /
• pp.62-84
• /
• 2010

Accurate forecasting of volatility is of considerable interest in financial volatility research, particularly in regard to portfolio allocation, option pricing and risk management because volatility is equal to market risk. So, we attempted to delineate a model with good ability to forecast and identified stylized features of volatility, with a focus on volatility persistence or long memory in the Australian futures market. In this context, we assessed the long-memory property in the volatility of index futures contracts using three conditional volatility models, namely the GARCH, IGARCH and FIGARCH models. We found that the FIGARCH model better captures the long-memory property than do the GARCH and IGARCH models. Additionally, we found that the FIGARCH model provides superior performance in one-day-ahead volatility forecasts. As discussed in this paper, the FIGARCH model should prove a useful technique in forecasting the long-memory volatility in the Australian index futures market.

• Journal of Korean Society for Quality Management
• /
• v.46 no.4
• /
• pp.959-972
• /
• 2018

Purpose: This study developed a simulation model that incorporates the uncertainty of demand and yield to obtain optimized results for supply chain coordination within environmental constraints. The objective of this study is to examine whether yield management for perishable products can achieve the goal of supply chain coordination between a single buyer and a single supplier under a variety of environmental conditions. Methods: We investigated the efficiency of a revenue-sharing contract and a wholesale price contract by considering demand and yield uncertainty, profit maximizing ratio, and success ratio. The implications for environmental variation were derived through a comparative analysis between the wholesale price contract and the revenue-sharing contract. We performed Monte Carlo simulations to give us the results of an optimized supply chain within the environments defined by the experimental factors and parameters. Results: We found that a revised revenue-sharing contracting model was more efficient than the wholesale price contract model and allowed all members of the supply chain to achieve higher profits. First, as the demand variation (${\sigma}$) increased, the profit of the total supply chain increased. Second, as the revenue-sharing ratio (${\Phi}$) increased, the profits of the manufacturer gradually decreased, while the profits of the retailer gradually increased, and this change was linear. Third, as the quality of yield increased, the profits of suppliers appear to increased. At last, success rate was expressed as the profit increased in the revenue-sharing contract compared to the profit increase in the wholesale price contract. Conclusion: The managerial implications of the simulation findings are: (1) a strategic approach to demand and yield uncertainty helps in efficient resource utilization and improved supply chain performance, (2) a revenue-sharing contract amplifies the effect of yield uncertainty, and (3) revised revenue-sharing contracts fetch more profits for both buyers and suppliers in the supply chain.

• International Area Studies Review
• /
• v.14 no.2
• /
• pp.25-40
• /
• 2010

Accurate forecasting of volatility is of considerable interest in financial volatility research, particularly in regard to portfolio allocation, option pricing and risk management because volatility is equal to market risk. So, we attempted to delineate a model with good ability to forecast and identified stylized features of volatility, with a focus on volatility persistence or long memory in the Australian futures market. In this context, we assessed the long-memory property in the volatility of index futures contracts using three conditional volatility models, namely the GARCH, IGARCH and FIGARCH models. We found that the FIGARCH model better captures the long-memory property than do the GARCH and IGARCH models. Additionally, we found that the FIGARCH model provides superior performance in one-day-ahead volatility forecasts. As discussed in this paper, the FIGARCH model should prove a useful technique in forecasting the long-memory volatility in the Australian index futures market.

• International conference on construction engineering and project management
• /
• 2009.05a
• /
• pp.622-627
• /
• 2009

Business process engineering (BPE) is a top-down management approach for increasing efficiency and productivity through radical and fundamental changes to the business processes of the organization. BPE requires firms to initially develop a model of the existing business processes of the firm to distinguish functional tasks from processes used for coordinating inputs, activities and outputs. The model is used for understanding the business processes in the organization and to simulate the effect of changes to the processes. The model can also be used to justify business processes, which involves assessing whether the business process provides value to the customer in its current configuration. Justification requires a careful examination of the key business processes used by the firm to identify systemic shortcomings in the process and to create a new business process to produce greater efficiency. BPE also considers automating as many business processes as possible to increase operational efficiency and the integration of business process tasks. The construction industry has been slow to adopt BPE because of its project approach in which a major firm contracts with various functional service providers and regards each project as unique. The industry focuses on functional task efficiency rather than business process efficiency. There is no formal methodology or criteria for determining whether a business process is effective for a construction firm in its current configuration. The use of performance measures such as costs, task duration times or other metrics can be useful in evaluating the effectiveness of an existing business process and for modeling the possible outcome of a fundamental and radical change to the process.

• International conference on construction engineering and project management
• /
• 2022.06a
• /
• pp.304-311
• /
• 2022

Construction inspection is a crucial stage that ensures that all contractual requirements of a construction project are verified. The construction inspection capabilities among state highway agencies have been greatly affected due to budget reduction. As a result, efficient inspection practices such as risk-based inspection are required to optimize the use of limited resources without compromising inspection quality. Automated prioritization of textual requirements according to their criticality would be extremely helpful since contractual requirements are typically presented in an unstructured natural language in voluminous text documents. The current study introduces a novel model for predicting the risk level of requirements using machine learning (ML) algorithms. The ML algorithms tested in this study included naïve Bayes, support vector machines, logistic regression, and random forest. The training data includes sequences of requirement texts which were labeled with risk levels (such as very low, low, medium, high, very high) using the fuzzy logic systems. The fuzzy model treats the three risk factors (severity, probability, detectability) as fuzzy input variables, and implements the fuzzy inference rules to determine the labels of requirements. The performance of the model was examined on labeled dataset created by fuzzy inference rules and three different membership functions. The developed requirement risk prediction model yielded a precision, recall, and f-score of 78.18%, 77.75%, and 75.82%, respectively. The proposed model is expected to provide construction inspectors with a means for the automated prioritization of voluminous requirements by their importance, thus help to maximize the effectiveness of inspection activities under resource constraints.