Development of a model for failure prediction on critical equipment in the petrochemical industry

In this study, a mathematical model was developed for failure prediction on critical equipment in petrochemical industry. The model utilized three principal measurements, namely: temperature, vibration and pressure, in developing a framework for determining expected failure periods for each component of the critical equipment. Validation of the model was done using data collected from Warri Refinery and Petrochemical Company, carbon black plant, Ekpan–Warri, Nigeria. Condition monitored data based on the three principal measurements were generated and used to determine expected failure periods for each component of the critical equipment (single-stage centrifugal compressor) in the plant. It was observed that for all the equipment under consideration, the life expectancy for blower casing is longest for all components, while that of gear and gear bearing is least. Hence, special attention should be focused on monitoring the condition of the gear and its bearing components. It was also observed from the plot trends that the deterioration rate of all components is affected by the equipment operating speed condition and functionality.     

In-depth analysis of the causal factors of incidents reported in the Greek petrochemical industry

This paper presents a statistical analysis of all reported incidents in the Greek petrochemical industry from 1997 to 2003. A comprehensive database has been developed to include industrial accidents (fires, explosions and substance releases), occupational accidents, incidents without significant consequences and near misses. The study concentrates on identifying and analyzing the causal factors related to different consequences of incidents, in particular, injury, absence from work and material damage. Methods of analysis include logistic regression with one of these consequences as dependent variable. The causal factors that are considered cover four major categories related to organizational issues, equipment malfunctions, human errors (of commission or omission) and external causes. Further analyses aim to confirm the value of recording near misses by comparing their causal factors with those of more serious incidents. The statistical analysis highlights the connection between the human factor and the underlying causes of accidents or incidents.     

Global optimization for signomial discrete programming problems in engineering design

This paper proposes a novel method to solve signomial discrete programming (SDP) problems frequently occurring in engineering design. Various signomial terms are first convexified following different strategies. The original SDP program is then converted into a convex integer program solvable by commercialized packages to obtain globally optimal solutions. Compared with current SDP methods, the proposed method is guaranteed to converge to a global optimum, is computationally more efficient, and is capable of treating zero boundary problems. Numerical examples are presented to demonstrate the usefulness of the proposed method in engineering design.     

Statistical analysis of major accidents in petrochemical industry notified to the major accident reporting system (MARS)

The European major accident reporting system (MARS) was created within the framework of European Union (EU) directive 82/501, the so-called "SEVESO" directive, and in order to register all the major industrial accidents notified to the European Union authorities from the member states. Statistical analysis of these accidents offers significant data to the understanding and prevention of industrial accidents. This paper makes an analysis of some characteristics of major accidents in the petrochemical sector included in MARS. The statistical analysis focused on the main categorization fields of the MARS short reports and additionally a refinement of the immediate causes of major accidents with focus on the organizational factors was attempted through the details provided in the full reports of the database.     

An integrated system solution for supply chain optimization in the chemical process industry

This paper considers a complex scheduling problem in the chemical process industry involving batch production. The application described comprises a network of production plants with interdependent production schedules, multi-stage production at multi-purpose facilities, and chain production. The paper addresses three distinct aspects: (i) a scheduling solution obtained from a genetic algorithm based optimizer, (ii) a mechanism for collaborative planning among the involved plants, and (iii) a tool for manual updates and schedule changes. The tailor made optimization algorithm simultaneously considers alternative production paths and facility selection as well as product and resource specific parameters such as batch sizes, and setup and cleanup times. The collaborative planning concept allows all the plants to work simultaneously as partners in a supply chain resulting in higher transparency, greater flexibility, and reduced response time as a whole. The user interface supports monitoring production schedules graphically and provides custom-built utilities for manual changes to the production schedule, investigation of various what-if scenarios, and marketing queries. RID="*" ID="*" The authors would like to thank Hans-Otto Günther and Roland Heilmann for helpful comments on draft versions of this paper.     

An automatic optimization method for minimizing supporting structures in additive manufacturing

The amount of supporting structure usage has been a major research topic in layer-based additive manufacturing (AM) over the past years as it leads to increased fabrication time and decreased surface quality. Previous studies focused on deformation and topology optimization to eliminate the number of support structures. However, during the actual fabrication process, the properties of shape and topology are essential. Therefore, they should not be modified casually. In this study, we present an optimizer that reduces the number of supporting structures by identifying the prime printing direction. Without rotation, models are projected in each direction in space, and the basis units involved in the generation of support structures are separated. Furthermore, the area of the supporting structures is calculated. Eventually, the prime printing direction with minimal supporting area is obtained through pattern-searching method. The results of the experiment demonstrated that the printing area was reduced by up to 60% for some cases, and the surface quality was also improved correspondingly. Furthermore, both the material consumption and fabrication time were decreased in most cases. In future work, additional factors will be considered, such as the height of the supporting structures and the adhesion locations to improve the efficiency of this optimizer.The full text can be downloaded at https://link.springer.com/content/pdf/10.1007%2Fs40436-019-00277-y.pdf     

军事冲突中战术欺骗的一个优化模型

军事冲突中实施战术欺骗已成为信息战的一个重要手段．基于军事冲突中战术欺骗所要达到的目标以及欺骗手段的资源约束和效果影响，建立了一个使军事欺骗总体效能达到最大的战术欺骗优化模型．给出的一个应用例子说明了该模型和方法的可行性．     

An integrated DEMATEL-MMDE-ISM based approach for analysing the barriers of IoT implementation in the manufacturing industry

Incorporation of smart devices within the older framework has brought along significant challenges. This paper presents a detailed analysis of the barriers faced during the implementation of Internet of Things (IoT) within the manufacturing sector. In addition, the authors aim to obtain a hierarchical structure, which will help the policymakers to identify the most crucial barriers enabling them to make an informed decision. With the help of databases like Scopus, Web of Science, etc. a comprehensive list of 22 barriers was initially obtained. This list was further narrowed down to 10 critical barriers. The first step of the analysis involved the application of Decision Making Trial and Evaluation Laboratory (DEMATEL) technique, which quantifies the influence of the barriers amongst one another. Maximum Mean De-Entropy (MMDE) technique is then used to obtain a scientific threshold value, which is later used in the Interpretive Structural Modelling (ISM) technique from which a hierarchical structure of the barriers is obtained. The results of this study are expected to highlight the most crucial barriers wherein the researchers and practitioners can focus their strategic efforts. This will facilitate the addressal of implicit issues while implementing IoT Techniques in the manufacturing industry.     

The impact of technology development on the future of the labour market in the Slovak Republic

One of the current open labour market issues is to analyze how the technology progress in production processes will affect the labour market, especially in the context of the replacement of human workers with machines. This paper aims to identify potential threats faced by the labour market in Slovakia, which based on the analysis, employs a significant number of workers in areas susceptible to automation. According to the results, industrial production in Slovakia is divided into several areas, where almost 41% of all industrial workers are employed in the manufacture of metal constructions, machinery and equipment, motor vehicles, semitrailers and trailers and the number of people employed in this sector is increasing linearly over the reference period from 2008 to 2016. The paper focuses on potential scenarios that may arise in the labour market in the near future, using Cobb-Douglas production function. In the original model, the production function of the company is based on production factors in which labour plays an important role. However, with the growth of automation, the original model of companies is changing, transforming, and workforce who has played the key role in the production process of goods or services are becoming redundant due to the growing autonomy of machines. The analyzed scenarios show situations that may arise in the labour market if a company changes the scale of the use of production factors in its production process. In other words, given the current situation as labour costs increase, the power and capabilities of machines are growing and a company wants to stay competitive on the global market.     

An optimization model for storage yard management in transshipment hubs

This paper studies a yard storage allocation problem in a transshipment hub where there is a great number of loading and unloading activities. The primary challenge is to efficiently shift containers between the vessels and the storage area so that reshuffling and traffic congestion is minimized. In particular, to reduce reshuffling, a consignment strategy is used. This strategy groups unloaded containers according to their destination vessel. To reduce traffic congestion, a new workload balancing protocol is proposed. A mixed integer-programming model is then formulated to determine the minimum number of yard cranes to deploy and the location where unloaded containers should be stored. The model is solved using CPLEX. Due to the size and complexity of this model two heuristics are also developed. The first is a sequential method while the second is a column generation method. A bound is developed that allows the quality of the solution to be judged. Lastly, a numerical investigation is provided and demonstrates that the algorithms perform adequately on most cases considered.     

Delineating development trends of nanotechnology in the semiconductor industry: Focusing on the relationship between science and technology by employing structural topic model

The bibliometrics research on nanotechnology highlights close interrelationships between scientific and technological activities (S&T) in the field of nanotechnology. Notwithstanding abundant empirical evidence on the mutual relations between S&T, the dynamics of the relationship from a contextual perspective have gained relatively little attention. Accordingly, our understanding of how science- and technology-oriented nanotechnology identifies development opportunities from each other is still at a nascent stage. To address this gap, by focusing on nanotechnology in the semiconductor industry, we use structural topic model to empirically explore the dynamic interrelationships between science- and technology-oriented nanotechnology. We empirically delineate the dynamic development trends in the context of the interrelationships between S&T and demonstrate how development opportunities are identified from each other. These findings show a new window of opportunities for how state-of-the-art models for semantic analysis can be used in the literature on S&T interrelationships.     

我国纸浆模塑工业包装的现状与发展

叙述了纸浆模塑技术在我国工业包装领域的应用现状及发展，并结合典型工艺与设备讨论了该技术的应用技术要点。     

A reliability model for assessing the risk of termite attack on housing in Australia

This paper describes a reliability model that was developed to estimate the risk of a successful termite attack on a house in Australia. The model of termite attack was based on the use of information obtained from a national database and on a formal survey of expert opinion. This information was embedded in a reliability model that is used to predict risk. Such models are an essential component of risk management strategies.     

Fuzzy Based Decision Making Approach for Evaluating the Severity of COVID-19 Pandemic in Cities of Kingdom of Saudi Arabia

The World Health Organization declared COVID-19 a pandemic on March 11, 2020 stating that it is a worldwide danger and requires imminent preventive strategies to minimise the loss of lives. COVID-19 has now affected millions across 211 countries in the world and the numbers continue to rise. The information discharged by the WHO till June 15, 2020 reports 8,063,990 cases of COVID-19. As the world thinks about the lethal malady for which there is yet no immunization or a predefined course of drug, the nations are relentlessly working at the most ideal preventive systems to contain the infection. The Kingdom of Saudi Arabia (KSA) is additionally combating with the COVID-19 danger as the cases announced till June 15, 2020 reached the count of 132,048 with 1,011 deaths. According to the report released by the KSA on June 14, 2020, more than 4,000 cases of COVID-19 pandemic had been registered in the country. Tending to the impending requirement for successful preventive instruments to stem the fatalities caused by the disease, our examination expects to assess the severity of COVID-19 pandemic in cities of KSA. In addition, computational model for evaluating the severity of COVID-19 with the perspective of social influence factor is necessary for controlling the disease. Furthermore, a quantitative evaluation of severity associated with specific regions and cities of KSA would be a more effective reference for the healthcare sector in Saudi Arabia. Further, this paper has taken the Fuzzy Analytic Hierarchy Process (AHP) technique for quantitatively assessing the severity of COVID-19 pandemic in cities of KSA. The discoveries and the proposed structure would be a practical, expeditious and exceptionally precise evaluation system for assessing the severity of the pandemic in the cities of KSA. Hence these urban zones clearly emerge as the COVID-19 hotspots. The cities require suggestive measures of health organizations that must be introduced on a war footing basis to counter the pandemic. The analysis tabulated in our study will assist in mapping the rules and building a systematic structure that is immediate need in the cities with high severity levels due to the pandemic.     

The social shaping of educational technologies in Saudi Arabia: An examination of how the social fabric shapes the construction and use of technologies

This article is organised around the research question: To what extent has the social fabric shaped the way in which educational technologies are constructed at the institutional level in a specific social context? This question is addressed through a naturalistic study of a state university in the Eastern Province of Saudi Arabia. Guided by the grounded theory approach, the data analysis demonstrated that Saudi society was committed to many established relationships, structures and identities, a commitment that has resulted in the social shaping of educational technologies.     

An analysis of designing for quality in the automotive industry

The paper is based on the authors' experiences in devising and conducting continuing education courses on Designing for Quality for design, development and manufacturing engineers in a large automotive company. Participants in the courses brought forward a wide range of quality problems encountered in their day-to-day professional activities. Methods for classifying and defining these problems are developed as a prelude to examination of the product development process and its management to fulfil quality objectives. The technique of quality function deployment which has recently received wide publicity in automotive engineering is investigated in the context of established design theory. Conclusions are drawn relating to the practice of engineering design in industry and the need for the effective dissemination of the work of design researchers.     

The disruptive mobile wallet in the hospitality industry: An extended mobile technology acceptance model

Given that the mobile wallet has become a disruptive innovation, especially in the Malaysian hospitality industry, this study investigates the adoption of mobile wallet in the hospitality industry among consumers. Different from the extant literature, this study extends the newly proposed mobile technology acceptance model with self-efficacy theory, critical mass theory, and flow theory to explain the behavioural intention to adopt. A self-administered questionnaire was utilised to collect data from mobile wallet users who have used a mobile wallet while dining out in restaurants and cafes. Other than technology self-efficacy and perceived critical mass, mobile usefulness, mobile ease of use, mobile self-efficacy, and perceived enjoyment were discovered to have a positive and significant association with the behavioural intention to adopt mobile wallet in the hospitality industry. The findings also suggested there were interrelationships between the constructs employed. Overall, the extended model was able to explain 61% of the variance in behavioural intention to adopt mobile wallet.     

An AHP-based multi-criteria model for assessment of the social sustainability of technology management process: A case study in banking industry

The abrupt development of technology has confronted different industries' managers with crucial decision points. The scope of their decisions' impact goes beyond their companies' borders. Sustainable assessment of technology investigates the economic, environmental, and social effects of technologies on firms and their environment. Nonetheless, the technology management process includes different steps (such as technology acquisition and exploitation) which need a comprehensive decision-making tool toward sustainable development targets. This paper aims to propose an integrated decision-making model to investigate the social sustainability of the technology management process. Considering three main steps of the technology management process (technology selection, technology acquisition, and technology exploitation), we constructed our model utilizing the Analytic Hierarchy Process (AHP) as one of the most popular decision-making tools. In order to evaluate the efficiency of the model, we implemented it for E-banking technologies in one of the oldest banks of Iran (Iran's AgriBank). The results indicated that internet banking, internal R&D, and internal exploitation are the best decision alternatives among the technology management process from the social sustainability perspective. The results were validated by calculating the Consistency Rate (CR) and performing scenario-based sensitivity analysis.     

Methodology for the simultaneous optimization of location and parameters of friction dampers in the frequency domain

It is well known that the use of passive energy dissipation devices such as friction dampers reduces the dynamic response of structures subjected to earthquakes. However, the parameters of each damper as well as the best position of these devices in the structure remain difficult to determine. Although articles on optimum design of tuned mass dampers and viscous dampers have been published, there is a lack of studies on the optimization of friction dampers. In previous contributions, the authors proposed a method for optimum design of this kind of damper. The proposed method is very useful; however, the computational time required is high. Thus, in this article, a new methodology for the simultaneous optimization of placement and forces of friction dampers is proposed. As this new method is developed in the frequency domain, the computational time is considerably reduced. For this purpose, the search group algorithm, recently developed by the authors, is employed, which is able to deal with optimization problems involving mixed discrete and continuous variables. For illustrative purposes, a six-storey shear building is analysed. Forces and positions of friction dampers are the design variables, while the objective function is to minimize the root mean square displacement at the top of the building. The results showed the excellent performance of the proposed method, reducing the root mean square displacement by more than 82%, with only three friction dampers and in a relatively short computational time.     

An ontology framework for developing platform-independent knowledge-based engineering systems in the aerospace industry

This paper presents the development of a novel knowledge-based engineering (KBE) framework for implementing platform-independent knowledge-enabled product design systems within the aerospace industry. The aim of the KBE framework is to strengthen the structure, reuse and portability of knowledge consumed within KBE systems in view of supporting the cost-effective and long-term preservation of knowledge within such systems. The proposed KBE framework uses an ontology-based approach for semantic knowledge management and adopts a model-driven architecture style from the software engineering discipline. Its phases are mainly (1) Capture knowledge required for KBE system; (2) Ontology model construct of KBE system; (3) Platform-independent model (PIM) technology selection and implementation and (4) Integration of PIM KBE knowledge with computer-aided design system. A rigorous methodology is employed which is comprised of five qualitative phases namely, requirement analysis for the KBE framework, identifying software and ontological engineering elements, integration of both elements, proof of concept prototype demonstrator and finally experts validation. A case study investigating four primitive three-dimensional geometry shapes is used to quantify the applicability of the KBE framework in the aerospace industry. Additionally, experts within the aerospace and software engineering sector validated the strengths/benefits and limitations of the KBE framework. The major benefits of the developed approach are in the reduction of man-hours required for developing KBE systems within the aerospace industry and the maintainability and abstraction of the knowledge required for developing KBE systems. This approach strengthens knowledge reuse and eliminates platform-specific approaches to developing KBE systems ensuring the preservation of KBE knowledge for the long term.