Ranking of vitrified grinding wheel parameters by using analytical hierarchical process (AHP) for surface roughness of work piece in grinding operation

Objective of grinding process is to generate high quality surface finish on work piece. There are many parameters which influence on the work piece roughness. Work piece material and characteristics, grinding wheel specification, grinding conditions and dressing conditions influence on the surface quality of the work piece. Selection of grinding wheel is important aspect for producing good quality of surface finish on the work piece. The main components of grinding wheel are the abrasive grains, bond material and porosity. Selection of correct grinding wheel is necessary for generating better surface finish on the work piece. Analytical Hierarchical Process (AHP) is used for ranking of vitrified bond grinding wheel parameters on surface roughness on the work piece in sub sequent grinding operation. The grit, grade, (Hardness of wheel) structure and type of abrasive are critically assisted in terms of the surface finish produced on work piece in the subsequent grinding operation. Analytic Hierarchy Process (AHP) shows that the abrasive grit of grinding wheel has first rank and grade (hardness) of the wheel has Second rank for the producing surface finish on the work piece after grinding operation. Structure and type of abrasive of wheel have a third and fourth rank respectively. Thus, AHP gives qualitative way of controlling work piece surface roughness in sub-sequent grinding operation by selecting proper grinding wheel of vitrified bond which helps the user to select the correct grinding wheel

Contractors Perspective on the Selection of Innovative Sustainable Technologies for Achieving Zero Carbon Retail Buildings

The use of innovative sustainable technologies (IST) has been regarded as an effective approach to enhancing energy efficiency and reducing carbon emissions of buildings. However, contractors face significant challenges in the selection of IST. The reported challenges in the literature include: lack of skills and knowledge, uncertainties, risks and the rapid development of a large number of technological alternatives and decision criteria. The selection process emerges as a multi-attribute, value-based task that includes both qualitative and quantitative factors, which are often assessed with imprecise data and human judgments. This paper aims to establish the decision criteria for the selection of IST for achieving low carbon existing retail buildings with a focus on the main contractor’s perspective. The arguments are informed by the combination of literature review and an in-depth case study with a UK leading contractor. Five broad decision criteria are identified systematically drawing on the contractor’s practice. The established criteria are weighted and ranked using the analytic hierarchy process and expert opinions; with ‘margin opportunity’ being the most important, followed by ‘repeat business’, ‘investment costs’, ‘differentiation’ and then ‘transferability’. The findings should facilitate the integration of various facets of the selection process and stimulate contractors to use IST

Analyzing the influential factors of industry 4.0 in precision machinery industry

Abstract. Nowadays the science and technology progresses not only create the change to have a big impact on various industries, but also stimulate Industry 4.0 being applied in the manufacturing industry to achieve manufacturing efficiency and to reduce its cost to increase additional values. This study uses the Analytical Hierarchical Process (AHP) evaluation method, which considers four criteria layers: Internet of things factors, Automationfactors, Intelligent factors, Big data factors, and twelve influence factors in sub-layer are: perceived layer, network layer, application layer, field layer, management layer, control layer, process control visualization, system supervisory and control omni bearing, green energy manufacturing production, variety, volume, and velocity. Then, the relative risk indicator (RRI) is obtained by the Analytical Hierarchical Process method, and the overall risk indicator (ORI) can be obtained after introducing the evaluation value of each impact factor through the case. The research results confirm that the risk assessment values obtained the hierarchical analysis method are consistent. This research through the Analytic Hierarchy Process, then discusses Industry 4.0 pair of Taiwan's precision machinery industry management pattern institute emphatically face with target, expected will provide the existing machine manufacture industry as well as the future wants to invest the precision machine industry the management policy-maker reference value, also might take the government policy consideration factors and the machine manufacture industry scholars study the academic for reference.Keywords. Industry 4.0, Precision machine industry, Analytic Hierarchy Process.JEL. L22, M11, O14

Agent and cyber-physical system based self-organizing and self-adaptive intelligent shopfloor

The increasing demand of customized production results in huge challenges to the traditional manufacturing systems. In order to allocate resources timely according to the production requirements and to reduce disturbances, a framework for the future intelligent shopfloor is proposed in this paper. The framework consists of three primary models, namely the model of smart machine agent, the self-organizing model, and the self-adaptive model. A cyber-physical system for manufacturing shopfloor based on the multiagent technology is developed to realize the above-mentioned function models. Gray relational analysis and the hierarchy conflict resolution methods were applied to achieve the self-organizing and self-adaptive capabilities, thereby improving the reconfigurability and responsiveness of the shopfloor. A prototype system is developed, which has the adequate flexibility and robustness to configure resources and to deal with disturbances effectively. This research provides a feasible method for designing an autonomous factory with exception-handling capabilities

Wireless Sensor Technology Selection for I4.0 Manufacturing Systems

The term smart manufacturing has surfaced as an industrial revolution in Germany known as Industry 4.0 (I4.0); this revolution aims to help the manufacturers adapt to turbulent market trends. Its main scope is implementing machine communication, both vertically and horizontally across the manufacturing hierarchy through Internet of things (IoT), technologies and servitization concepts. The main objective of this research is to help manufacturers manage the high levels of variety and the extreme turbulence of market trends through developing a selection tool that utilizes Analytic Hierarchy Process (AHP) techniques to recommend a suitable industrial wireless sensor network (IWSN) technology that fits their manufacturing requirements.In this thesis, IWSN technologies and their properties were identified, analyzed and compared to identify their potential suitability for different industrial manufacturing system application areas. The study included the identification and analysis of different industrial system types, their application areas, scenarios and respective communication requirements. The developed tool’s sensitivity is also tested to recommend different IWSN technology options with changing influential factors. Also, a prioritizing protocol is introduced in the case where more than one IWSN technology options are recommended by the AHP tool.A real industrial case study with the collaboration of SPM Automation Inc. is presented, where the industrial systems’ class, communication traffic types, and communication requirements were analyzed to recommend a suitable IWSN technology that fits their requirements and assists their shift towards I4.0 through utilizing AHP techniques. The results of this research will serve as a step forward, in the transformation process of manufacturing towards a more digitalized and better connected cyber-physical systems; thus, enhancing manufacturing attributes such as flexibility, reconfigurability, scalability and easing the shift towards implementing I4.0

Magnetic field measurement from 132 kv and 275 kv overhead transmission lines within residential area

Overhead transmission line (OTL) has been around for so many years as one of the most important elements of electric power systems. Conductors, as being a part of the medium to transfer electricity through the OTL, produces electromagnetic field to its surrounding that have been a public concern for ages. OTL were meant to be built as far away from a population. Though from time to time, the OTL rights-of-way (ROW) were violated due to lack of space and rapid urbanization. This paper addresses the challenges faced during magnetic field level measurement within a residential area that was still under construction. EMDEX II Meter, Linear Data Acquisition System (LINDA) Wheel and Gauss Meter were used during the magnetic field measurements. Maximum magnetic field level data collected from measurement were presented

A generalizable method and case application for development and use of the Aviation Systems – Trust Survey (AS-TS).

Automated systems are integral in the development of modern aircraft, especially for complex military aircraft. Pilot Trust in Automation (TIA) in these systems is vital for optimizing the pilot-vehicle interface and ensuring pilots use the systems appropriately to complete required tasks. The objective of this research was to develop and validate a TIA scale and survey methodology to identify and mitigate trust deficiencies with automated systems for use in Army Aviation testing. There is currently no standard TIA assessment methodology for U.S. Army aviation pilots that identifies trust deficiencies and potential mitigations. A comprehensive literature review was conducted to identify prominent TIA factors present in similar studies. The compiled list of factors and associated definitions were used in a validation study that utilized the Analytic Hierarchy Process (AHP) as a pair-wise comparison tool to identify TIA factors most relevant to Army pilots. A notional survey, the Aviation Systems – Trust Survey (AS-TS), was developed from the identified factors and pilots were used as subjects in scenario-based testing to establish construct validity for the survey. Exploratory factor analysis was conducted after data collection and a validated survey was produced. A follow-on study interviewed Army test and evaluation experts to refine the survey methodology and ensure appropriate context for the recommended mitigations. A final packet was developed that included instructions for the rating scale, associated item definitions, and recommended mitigations for trust deficiencies. Future research will focus on other Army demographics to determine the generalizability of the AS-TS

Industry 4.0 implementation strategy for Small Medium Enterprises

I4.0 implementation strategy is a tool that aids small and medium enterprises to meet the fourth industrial revolution pre-requisites and standards. The main objective of the current research that has been achieved is that it established an industry 4.0 implementation strategy for SMEs, that is capable of providing enterprises with the most effective road map to overcome the obstacles faced by SMEs during transformation and accomplish the fourth industrial revolution’s standards. A roadmap and the implementation strategy will be specifically tailored to the participating enterprise, based on their assessment scores. The implementation strategy requires four consecutive steps including Maturity Assessment, Influence Assessment, Roadmap Construction, and Implementation. An Industry 4.0 implementation strategy has been devised to increase the accuracy of assessing SME’s technological maturity level by providing a weighting factor for relevant implementation dimensions by using an Analytic hierarchy process (AHP). Weight factors were established to identify dimensions that are most influential at small/medium manufacturing enterprises and prioritize their transformation. A total maturity score of the enterprise as a whole valued between 0-100 is determined at the end of the maturity assessment through utilizing radar charts. This research includes a case study that was conducted at SPM Automation Inc., a local small-sized enterprise, where the proposed four-step implementation strategy was conducted and succeeded to measure the current I4.0 maturity score which was 33% and create an implementation strategy that targets the most influential dimensions and prioritize their transformation

Enterprise Marketing Automation Software Selection

Enterprises devote a large amount of time and effort in selecting software products that are critical to their competitive advantage, and one such software is the marketing automation software. The paper discusses in detail the different criteria and methodology for selecting one marketing automation software product among the leading products available in the market. The selection process was identified as a multi-criteria decision-making (MCDM) problem and the methodology used for analysis was Hierarchical Decision Model (HDM), a variation of Analytic Hierarchy Process (AHP). Nine experts with different backgrounds in terms of job functions, functional experience, and geographies, who had expertise in marketing automation tools or related products were requested to give their inputs for the HDM analysis and a detailed analysis was done on the results. The results pointed to a single product as the winner of the analysis which was found to reflect the market share and research data and helped understand the decision-making process under different preferences and perspective differences. For future research and further analysis, the model could be made more robust with the inputs from more number of experts to eliminate any bias or outliers and corroborating the results by independently analyzing it with different decision-making methodologies such as TOPSIS or DEA

Communication technology selection method for smart energy metering based on analytic hierarchy process

As new communication technologies continue to emerge and the integration of these technologies into the modernization of the electricity grid becomes increasingly necessary, a variety of communication protocols and combinations are being explored for their potential use in the smart grid domain. However, given the multitude of technological possibilities available, choosing the optimal technology capable of adequately addressing the communication requirements of the intelligent grid remains a challenge for utilities. This is due, on the one hand, to the fact that different intelligent grid applications have different qualitative and quantitative communication requirements. Moreover, on the other hand, each technology has advantages and disadvantages concerning its performance characteristics in such requirements. This work uses the AHP (Analytic Hierarchy Process) methodology to select the wireless technology that presents the best performance characteristics concerning determined requirements. For this, a computational algorithm was developed in the Matlab programming environment, through which criteria such as data rate, latency, range, security, reliability, and interoperability were compared to select the best technological alternative among Wi-Fi, ZigBee, Z-Wave, and Bluetooth. Data collected from the literature review, with the performance characteristics of these technologies, were applied in a single case study simulating the practical implementation of this work. Among the analyzed criteria, simulations demonstrated that Wi-Fi was the winning technology alternative with 32.353%, followed by Z-Wave with 29.865% in second place, and ZigBee and Bluetooth were ranked third and fourth with 25.255% and 12.527%, respectively. In addition, sensitivity analysis shows how the AHP methodology can be a feasible alternative to assist decision-making in the smart grid domain.À medida que novas tecnologias de comunicação continuam a surgir e a integração destas tecnologias na modernização da rede elétrica se torna cada vez mais necessária, uma variedade de protocolos e combinações de tecnologias de comunicação vem sendo explorados para a sua potencial utilização no domínio da rede inteligente. No entanto, dada a multiplicidade de possibilidades tecnológicas disponíveis, a escolha da melhor tecnologia capaz de responder, adequadamente, aos requisitos de comunicação da rede elétrica inteligente continua sendo um desafio para diferentes atores interessados. Isto se deve, por um lado, ao fato de diferentes aplicações de rede inteligente terem diferentes requisitos de comunicação, quer sejam quantitativos ou qualitativos. Além disso, por outro lado, cada tecnologia tem vantagens e desvantagens relacionadas com as suas características de desempenho em tais requisitos. Este trabalho, portanto, utiliza a metodologia AHP (Analytic Hierarchy Process) para selecionar a tecnologia sem fios que apresenta as melhores características de desempenho relativamente a determinados requisitos. Para tal, foi desenvolvido um algoritmo computacional no ambiente de programação Matlab, através do qual critérios tais como taxa de dados, latência, alcance, segurança, confiabilidade e interoperabilidade foram comparados para selecionar a melhor alternativa tecnológica entre Wi-Fi, ZigBee, Z-Wave e Bluetooth. Os dados coletados na revisão de literatura, com as características de desempenho destas tecnologias, foram aplicados num único estudo de caso simulando a implementação prática deste método em ambiente residencial. Dentre os critérios analisados, as simulações demonstraram que o Wi-Fi foi a alternativa tecnológica vencedora com 32,353%, seguido pelo Z-Wave com 29,865% em segundo lugar, e ZigBee e Bluetooth ficaram em terceiro e quarto lugar com 25,255% e 12,527%, respectivamente. Além disso, a análise de sensibilidade, dos resultados, mostra como a metodologia AHP pode ser uma alternativa viável para auxiliar na tomada de decisões no domínio da rede inteligente