The Measurement of Sustainable Regional Manufacturing Industry: The Case of China

Since the introduction of Made in China 2025 and its focus on sustainable development and manufacturing industry transformation, appropriate evaluation methods to accurately assess the development of China’s manufacturing industry have become essential. Therefore, this research constructed an innovative evaluation index system for manufacturing development based on seven dimensions: innovation, structural optimization, economic benefits, efficiency enhancements, green development, international competition, and social benefits. An objective combination weighted-gray correlation-TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) evaluation model was applied to the Sichuan Province manufacturing industry data from 2009 to 2018 to create a representative sample, in which the overall development level from 2009 to 2016 took on an inverted U-shaped curve that reached its maximum in 2013, fell to its lowest point in 2016, and then began a steady upward trend marked by innovation and efficiency improvements; however, sustainability fell. Based on these results, this research provides a scientific reference for policy-makers with recommendations for innovation-driven development strategies, green development promotion, and social benefit improvements with the aim of promoting more sustainable development of China's manufacturing industry.

Analysis of Driving Control Characteristics in Typical Road Types

Vehicle control requirements for longitudinal and lateral driver control are varied in different road geometries; this makes it irrational and superfluous to represent driving control characteristics with repetitive indices. To address this problem, the present study used multiple cross-analysis methods of vehicle running state parameters from experienced drivers in order to deeply study driving control characteristics in different road geometries. Six common road geometries with different driving control emphases were selected as typical road types and twenty-five experienced drivers were asked to perform an actual driving test. Taking the indices in the long straight road as the control variable, the indices in other roads were compared with it and judged according to the three methods: the overall distribution by box plots, significant difference test by analysis of variance (ANOVA) and relative distance calculation by technique for order preference by similarity to an ideal solution (TOPSIS). Moreover, the weight of the driving control characteristic index was calculated through the entropy weight method to reflect its importance. In this paper, the relationships between road geometry and driving control characteristics explicate the influence mechanism and interaction of road geometry on driving behavior, and the indicators that can reflect the control characteristics in different road types are obtained.

PACAM: A Pairwise-Allocated Strategy and Capability Average Matrix-Based Task Scheduling Approach for Edge Computing

With the development of the smart Internet of Things (IoT), an increasing number of tasks are deployed on the edge of the network. Considering the substantially limited processing capability of IoT devices, task scheduling as an effective solution offers low latency and flexible computation to improve the system performance and increase the quality of services. However, limited computing resources make it challenging to assign the right tasks to the right devices at the edge of the network. To this end, we propose a polynomial-time solution, which consists of three steps, i.e., identifying available devices, estimating device quantity, and searching for feasible schedules. In order to shrink the number of potential schedules, we present a pairwise-allocated strategy (PA). Based on these, a capability average matrix (CAM)-based index is designed to further boost efficiency. In addition, we evaluate the schedules by the technique for order preference by similarity to an ideal solution (TOPSIS). Extensive experimental evaluation using both real and synthetic datasets demonstrates the efficiency and effectiveness of our proposed approach.

Application of the Technique For Order Preference By Similarity To Ideal Solution Method in Determining Contract Employees to Become Permanent Employees

Refratech Mandala Perkasa (RMP) is a refractory cement manufacturing company. The company also operates in the manufacture of refractory cement made for repair of hot coatings, boilers, rotary kilns, incinerators, ovens and chemicals for steel metals, as well as ferrous & non ferrous foundries. In this company there are contract employees and permanent employees, contract employees are employees or workers whose working period is limited by a certain time according to the agreement within the company. While permanent employees are workers whose working period is approximately until they receive certain benefits according to the work agreement. This research was conducted to assist companies in decision support using the Topsis method in determining the appointment of contract employees to permanent employees based on predetermined criteria, namely Knowledge and Skills at work, Quantity and Quality of Work, Job Responsibilities, Initiatives in Work, and Compliance. on rules or discipline. The results of this study indicate that the determination of the ranking of prospective permanent employees can be obtained from the calculation results of the TOPSIS method, where the results of prospective employees are based on predetermined administrative criteria. Prospective permanent employees who have the highest rank have the right to be selected first. The accuracy of the implementation of the TOPSIS method on the system plays a major role in the effectiveness and efficiency of the company's services to consumers compared to before the system was implemented. With the implementation of this DSS system, it can help companies to make it easier to make decisions to survey prospective permanent employees and optimize employee performance.

Parametric analysis of dry machining process using a novel integrated multi-attribute decision making approach

In most of the machining processes, the complexity arises in the selection of the right process parameters, which influence the machining process and output responses such as machinability and surface roughness. In such situations, it is important to estimate the inter-relationships among the output responses. One such method, Decision-Making Trial and Evaluation Laboratory (DEMATEL) is applied to study the inter-relationships of the output responses. Estimation of proper weights is also crucial where the output responses are conflicting in nature. In the current study, DEMATEL technique is used for estimating the inter-relationships for output responses in machining of EN 24 alloy under dry conditions. CRiteria Importance Through Inter-criteria Correlation (CRITIC) method is used to estimate the weights and finally the optimal selection of machining parameters is carried out using Techniques for Order Preference by Similarity to an Ideal Solution (TOPSIS) method. The model developed guides the decision maker in selection of precise weights, estimation of the inter relationships among the responses and selection of optimal process parameters.

A Decision-Making Model of Technological-Focused Government Agency Selection of Technological Start-Up Businesses

In developing countries, the government has played an important role in supporting startup businesses in various aspects, primarily through tech-focused government agencies. With a limited budget, the government agencies are critical to select plenty of tech startups for funding, leaving only promising tech startups. Consequently, government agencies inevitably face decision-making problems under uncertain circumstances, like private equity investment situations. Reviewing the relevant decision-making frameworks has identified that a classical multiple criteria decision-making (MCDM) approach is currently used, assuming decision-makers acquire complete information that is not realistic. Moreover, both qualitative and quantitative criteria used in evaluating startup businesses cannot represent the uncertainty which is the fundamental nature of the decision-making circumstance. Thus, this article presents a decision-making framework of tech-focused government agencies for selecting startup businesses based on a fuzzy MCDM of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Besides, it identifies selection criteria with mixed research methodologies and determines weights of importance criteria by the Delphi method. Finally, the proposed framework results are fairness, transparency, and eliminating bias in decision-making, including more efficiency when the framework’s ranking orders significantly correspond with actual performances. HIGHLIGHTS Criteria for selecting start-up businesses in technological-focused government agencies A decision-making framework of tech-focused government agencies for selecting startup businesses based on a fuzzy MCDM of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) The performance of the decision-making framework in selecting startup businesses to acquire high potential tech startups to drive the national economy GRAPHICAL ABSTRACT

Key Drivers Of The Emergency Capabilities Of Integrated Elderly Services Supply Chains

This study investigated integrated elderly care services supply chains using a combination of Decision Making Trial and Evaluation Laboratory (DEMATEL), Interpretative Structural Modeling (ISM), and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), The research identifies the key factors related to the emergency response capabilities of elderly service supply chains and the most important ways to improve them. The integrated DEMATEL-ISM-TOPSIS method provides new theoretical support for the management of elderly care service supply chains.

Selection of 3D Printer for Innovation Centre of Academic Institution Based on AHP and TOPSIS Methods

This paper describes a computer-based tool for the selection of 3D printer for educational propose by using Multi Attribute Decision Making (MADM) strategies particularly Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). In education, 3D printing technologies facilitate improved learning, skills development, and increased student and teacher engagement with the subject matter. Furthermore, 3D printing sparks greater creativity and collaboration in solving problems, to settle on a best option for teaching learning process tasks into account. MADM methods are interpretative processes which are well suited in choice of different 3D printers. This work suggests AHP and TOPSIS to judge 3D printer alternatives for choice of method, based on the AHP and TOPSIS methodology, ranks available techniques by a score resulting from the composition of priorities at different levels, each considering homogeneous and independent evaluation criteria. In this work proposes a comprehensive list of key factors that have a significant influence on 3D printer selection. In this work type of material used for printing considered as common for all printers such as ABS (Acrylonitrile Butadiene Styrene), PLA (Polylactic Acid), PET or Polyethylene terephthalate etc. A total of 09 sub-criteria have been identified and grouped under three main criteria, namely, (i) Physical Characteristics (ii) Economic consideration, (iii) Operational Requirements. These entire criteria area unit extracted from on-line literature and skilled opinion. Result of study shows that 3D Printer one (ET4 PRO 3IDEA model) was designated because the best suited for Innovation Centre Academic Institution. Keywords: 3D printer, MADM method, AHP method, TOPSIS method, Innovation Centre, Academic Institution