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This paper aims to present the development and experimental study of a fully automated system using a novel laser additive manufacturing technology called laser foil printing (LFP), to fabricate metal parts layer by layer. The mechanical properties of parts fabricated with this novel system are compared with those of comparable methodologies to emphasize the suitability of this process.

Test specimens and parts with different geometries were fabricated from 304L stainless steel foil using an automated LFP system. The dimensions of the fabricated parts were measured, and the mechanical properties of the test specimens were characterized in terms of mechanical strength and elongation.

The properties of parts fabricated with the automated LFP system were compared with those of parts fabricated with the powder bed fusion additive manufacturing methods. The mechanical strength is higher than those of parts fabricated by the laser powder bed fusion and directed energy deposition technologies.

To the best knowledge of authors, this is the first time a fully automated LFP system has been developed and the properties of its fabricated parts were compared with other additive manufacturing methods for evaluation.

The purpose of this paper is to describe the development of a novel mobile monitoring and control (MC) framework with active-push and plug-and-play capabilities. This proposed framework is particularly designed to addresses the shortcomings of the traditional factory MC systems in sharing information over the internet, protecting the system security, delivering warning messages, and deploying monitoring points.

By leveraging web service technology, mobile devices, and wireless communication, this paper describes the methodology and approach for designing a MC server, a wireless monitoring module (WMM), an intelligent v-Machine, two active-push mechanisms, a pocket PC application, and a smart phone application.

The designed WMM enables the monitoring points to be deployed in a mobile manner. The proposed mobile MC framework (MMCF) can timely detect abnormalities of appliances and equipment and turn off appliances in dangerous situations through WMM. It can also instantly deliver various warning contents to the mobile devices carried by the responsible persons. The v-Machine is built based on virtual metrology (VM) technology and can predict production precision of machined workpieces.

With the successful design and testing of the novel MMCF, this framework can obviously be used for many more applications and developments.

The authors' implement a factory MC system based on the proposed framework and conduct various integration tests on two electric appliances and a practical CNC machine tool in a factory. Testing results shows that the factory MC system works smoothly according the design goals and can overcome the shortcomings of traditional factory MC systems. The MC system also presents good performances, instantly delivering warning contents with a size ranging from 1K bytes to 10M bytes to the users within few seconds.

The proposed MMCF exploits various automation technologies to detect equipment's abnormalities, reduce the rate of product defects caused by human errors, reinforce security, prevent accidents, and ensure the safety of operations.

The proposed MMCF can effectively promote existing factory MC systems to achieve the merits of mobile MC, which is a unique contribution of this work, compared to previous studies. The results of this study can be applied to a variety of industrial automation applications, including factory automation and assembly automation.

The purpose of this paper is to provide a concise overview of the problem of building decay in Hong Kong, the current government measures concerning dilapidated buildings and the latest development and implementation of the mandatory building inspection scheme (MBIS). A comparison of various MBISs from other jurisdictions of the world is also given.

A desktop study of building inspection procedures, repair and maintenance policies was carried out, followed by an industry-wide opinion survey conducted by means of self-administered questionnaires. Target respondents are within the construction community of Hong Kong. The perceived benefits, potential difficulties and insightful recommendations or good practices are investigated. A comparison of the relative ranking of individual mean scores from various groups of respondents is presented in this paper.

The execution of MBIS was found to be effective in enhancing public awareness of the importance of building upkeep and recognition of the property owner's legal responsibilities in this respect. Private property owners were made aware of the necessity to take holistic preventive measures to maintain the overall safety of their own buildings. A comparison of MBIS with other similar MBISs across different cities, revealed similarities as regards the inspection cycle, scope of inspection and qualifications of inspectors. The main difference related to the age rather than the height of target buildings.

Proper inspection and maintenance is necessary to keep buildings in good condition to avoid injury or loss of life due to sudden collapse of structures or their elements such as concrete spalling and fall of window frames. The official launch of MBIS on 30 June 2012 is one of the proposed effective measures to resolve the long-standing problems of building neglect and deterioration in Hong Kong with particular regard to the existing old private premises.

The execution of MBIS should be useful in improving the safety and health status of the dilapidated premises and in so doing safeguarding the residents and general public. To further identify the perceived benefits and potential difficulties of MBIS, and to suggest insightful recommendations or good practices for its successful future implementation, an opinion survey was launched among construction practitioners in Hong Kong between March and April of 2012.

The principal aim of this study was to provide more realistic output data based on imprecise measurements of product quality. The real‐world problems in fuzzy testing and selecting better processes performance are considered.

The Taguchi index, which provides numerical measures on process performance, has been widely used in the industry. In practice, the Taghchi index is estimated by sample data, thus it is of interest to obtain the confidence limits of the estimate C_pm for assessing processes. In addition, it is much more realistic, because in general the output quality characteristics of continuous quantities are more or less imprecise. Using the approach taken by Buckley, with some extensions, a general method is used to combine the vector of fuzzy numbers to produce the membership function of a fuzzy estimator of C_pm for further fuzzy testing and selection of better process performances.

As the rapid advancement of manufacturing technology occurs, current firms are increasing their levels of out sourcing and are relying more heavily on their supply chain as a source of their competitive advantage. Supplier selection decisions have become an important component of production and logistics management. Those decisions have a significant impact on manufacturers' ability to compete as purchases from outside suppliers may account for a large proportion of a product's costs.

The authors assume that measurements are taken from normally distributed populations in this research. Using fuzzy inference to assess manufacturing process capability processed using imprecise data under mild and severe departures from normality would be an interesting issue for further research.

From a managerial standpoint, considering stochastic uncertainty and fuzziness of data during testing and selecting the better supplier often provides a strong incentive to suppliers to adhere to the conscious gathering of data and variance reductions, as well as to quality requirements and standards.

An obvious advantage of process capability analysis over traditional classical approaches, which use binomial distribution for estimating low fractions of NC, is that reviewing a smaller sample reduces time, effort, and expenses.

The purpose of this paper is to apply social network analysis (SNA) to study faculty research productivity, to identify key leaders, to study publication keywords and research areas and to visualize international collaboration patterns and analyze collaboration research fields from all Management Information System (MIS) departments in Taiwan from 1982 to 2015.

The authors first retrieved results encompassing about 1,766 MIS professors and their publication records between 1982 and 2015 from the Ministry of Science and Technology of Taiwan (MOST) website. Next, the authors merged these publication records with the records obtained from the Web of Science, Google Scholar, IEEE Xplore, ScienceDirect, Airiti Library and Springer Link databases. The authors further applied six network centrality equations, leadership index, exponential weighted moving average (EWMA), contribution value and k-means clustering algorithms to analyze the collaboration patterns, research productivity and publication patterns. Finally, the authors applied D3.js to visualize the faculty members' international collaborations from all MIS departments in Taiwan.

The authors have first identified important scholars or leaders in the network. The authors also see that most MIS scholars in Taiwan tend to publish their papers in the journals such as Decision Support Systems and Information and Management. The authors have further figured out the significant scholars who have actively collaborated with academics in other countries. Furthermore, the authors have recognized the universities that have frequent collaboration with other international universities. The United States, China, Canada and the United Kingdom are the countries that have the highest numbers of collaborations with Taiwanese academics. Lastly, the keywords model, system and algorithm were the most common terms used in recent years.

This study applied SNA to visualize international research collaboration patterns and has revealed some salient characteristics of international cooperation trends and patterns, leadership networks and influences and research productivity for faculty in Information Management departments in Taiwan from 1982 to 2015. In addition, the authors have discovered the most common keywords used in recent years.

This paper aims to investigate the effects on material performance in the epoxy acrylate resin system owing to the existence of the different ring of the cyclic methacrylate. In this paper, cyclic methacrylate as diluents was added into epoxy acrylate (EA) resin by ultraviolet (UV)-cured polymerization to investigate the effects on material performance owing to the existence of the different rings.

EA and 1-adamantyl methacrylate were synthesized by traditional methods according to previous papers, respectively. After adding different cyclic methacrylate as diluents to the EA oligomers, the system was exposed to the UV-light for polymerization.

The hydrophobic properties of the cured materials were increased slightly because of the alkyl groups from the methacrylate. The thermal stabilities and mechanical properties of the resins were enhanced by the cyclic diluents with the hard segments. Meanwhile, the crosslink density of the polymer decreased with the bulky group like adamantly owing to its huge structure.

The cyclic methacrylates were introduced into EA oligomers for decreasing the viscosity and increasing the materials performances, which could be recognized as new diluents applied in UV-cued polymerization.

The results of this study will be conducive to fabricate EA resins possessed with high thermal stabilities and mechanical properties by convenient UV-cured polymerization.

In recent decades there has been much interest and activity in the application of mathematical ideas for controlling inventory. However most of this has been related to the control of stock products whose demand is smooth and continuous. When demand is lumpy these methods are inefficient in their attempts to minimise thé operating cost. A simple regression model is developed for computing optimal (s, S) policies for items with lumpy demand patterns. Continuous review of inventory level is assumed and the lead time demand is approximated by the stuttering Poisson distribution. A grid of 864 known optimal policies has been used to provide the data for the calibration of the regression models. Numerical models are used to illustrate this approach. Extensive computational results show that this model provides excellent performance in estimating the optimal values of the control parameters s and S for wide ranges of demand and cost parameters.

The study aims to investigate the profitability and marketability efficiency scores and determinants of 899 listed manufacturers in six Southeast Asian countries: Indonesia, Malaysia, the Philippines, Singapore, Thailand and Vietnam.

The study employs the bootstrap two-stage data envelopment analysis (DEA) to measure profitability and marketability efficiencies of Southeast Asian manufacturers. The study uses the panel-data fractional regression model (FRM), which is an advantageous method that is suitable for the fractional response variables and applicable to time-differing heterogeneity, to investigate the determinants of Southeast Asian manufacturers' efficiencies.

The study demonstrates that listed manufacturers in Indonesia and Singapore achieve the highest average profitability and marketability efficiencies among the six Southeast Asian countries. The study also shows that the cash ratio, institutional ownership, headcount and technology-application positively affect Southeast Asian-listed manufacturers' profitability and marketability efficiencies at different levels of significance.

The current study is the first assessment of the listed manufacturers' profitability and marketability efficiencies in Southeast Asian countries, which consist of different market levels (developed, emerging and frontier markets). The study is a reference source for regional investors, manufacturers' managers and governments to make appropriate decisions in investing, managing and enhancing the development of the Southeast Asian manufacturing sector.

The purpose of this paper is to analyze the fuzzy reliability of the compressor house unit (CHU) system in a coal fired thermal power plant under vague environment by reducing the accumulating phenomenon of fuzziness and accelerating the computation process. This paper uses different fuzzy membership functions to quantify uncertainty and access the system reliability in terms of different fuzzy reliability indices having symmetric shapes.

This study analyses the fuzzy reliability of the CHU system in a coal fired thermal power plant using T_ω-based generalized fuzzy Lambda-Tau (TBGFLT) technique. This approach applies fault tree, Lambda-Tau method, different fuzzy membership functions and α-cut coupled T_ω-based approximate arithmetic operations to compute various reliability parameters (such as failure rate, repair time, mean time between failures, expected number of failures, availability and reliability) of the system. The effectiveness of TBGFLT technique has been demonstrated by comparing the results with results obtained from four different existing techniques. Moreover, this paper applies the extended Tanaka et al. (1983) approach to rank the critical components of the system when different membership functions are used.

The adopted TBGFLT technique in the present study improves the shortcomings of the existing approaches by reducing the accumulating phenomenon of fuzziness, accelerating the computation process and getting symmetric shapes for computed reliability parameters when different membership functions are used to quantify data uncertainty.

In existing fuzzy reliability techniques which are developed for repairable systems either triangular fuzzy numbers, triangle vague sets or triangle intuitionistic fuzzy sets have been used for quantifying uncertainty. These approaches do not examine the systems for components with different membership functions. The present study is an effort in this direction and evaluates the fuzzy reliability of the CHU system in a coal fired thermal power plant for components with different membership functions. This is the main contribution of the paper.

This article examines the impact of three leadership styles as a predictor of job satisfaction in a state university system. The Multifactor Leadership Questionnaire was used to identify the leadership style of an administrator as perceived by faculty members. Spector’s Job Satisfaction Survey was used to assess a faculty member’s level of job satisfaction. The population consisted of 567 full-time faculty members, and 104 participants completed the survey. The results of logistic regression analysis revealed that (a) faculty members who identified transformational leadership as dominant had increased job satisfaction, (b) faculty members who identified transactional leadership as dominant had increased job satisfaction, and (c) faculty members who identified passive/avoidant leadership as dominant had decreased job satisfaction. Demographics did not appear to predict satisfaction. Using this model, academic leaders can take further action by refining their leadership styles on the basis of their faculty members’ indicated preferences. The study results may contribute to social change at the departmental level by making academic administrators aware of effective leadership models that promote higher job satisfaction among faculty in universities.