Multi-Agents System Approach to Industry 4.0: Enabling Collaboration Considering a Blockchain

Dissertação de Mestrado em Engenharia InformáticaThe evolution of existing technologies and the creation of new ones paved the way for a new revolution in the industrial sector. With the introduction of the existing and new technologies in the manufacturing environment, the industry is moving towards the fourth industrial revolution, called Industry 4.0. The fourth industrial revolution introduces many new components like 3D printing, Internet of things, artificial intelligence, and augmented reality. The automation of the traditional manufacturing processes and the use of smart technology are transforming industries in a more interconnected environment, where there is more transparent information and decentralised decisions. The arrival of Industry 4.0 introduces industries to a new environment, where their manufacturing processes are more evolved, more agile, and with more efficiency. The principles of Industry 4.0 rely on the interconnection of machines, devices, sensors, and people to communicate and connect. The transparency of information guaranties that decision makers are provided with clear and correct information to make informed decisions and the decentralisation of decisions will create the ability for machines and systems to make decisions on their own and to perform tasks autonomously. Industry 4.0 is making manufacturing processes more agile and efficient, but due to the fast pace of trends and the shift from the traditional mass production philosophy towards the mass customisation, following the Industry 4.0 guidelines might not be enough. The mass customisation paradigm was created from the desire that customers have in owning custom made products and services, tailor made to their needs. The idea to perform small tweaks in a product to face the needs of a consumer group, keeping the production costs like the ones from the mass production, without losing efficiency in the production. This paradigm poses great challenges to the industries, since they must be able to always have the capability to answer the demands that may arise from the preparation and production of personalised products and services. In the meantime, organisations will try to increasingly mark its position in the market, with competition getting less relevant and with different organisations worrying less with their performance on an individual level and worrying more about their role in a supply chain. The need for an improved collaboration with Industry 4.0 is the motivation for the model proposed in this work. This model, that perceives a set of organisations as entities in a network that want to interact with each other, is divided into two parts, the knowledge representation and the reasoning and interactions. The first part relies on the Blockchain technology to securely store and manage all the organisation transactions and data, guaranteeing the decentralisation of information and the transparency of the transactions. Each organisation has a public and private profile were the data is stored to allow each organisation to evaluate the others and to allow each organisation to be evaluated by the remainder of the organisations present in the network. Furthermore, this part of the model works as a ledger of the transactions made between the organisations, since that every time two organisations negotiate or interact in any way, the interaction is getting recorded. The ledger is public, meaning that every organisation in the network can view the data stored. Nevertheless, an organisation will have the possibility, in some situations, to keep transactions private to the organisations involved. Despite the idea behind the model is to promote transparency and collaboration, in some selected occasions organisations might want to keep transactions private from the other participants to have some form of competitive advantage. The knowledge representation part also wants to provide security and trust to the organisation that their data will be safe and tamper proof. The second part, reasoning and interactions, uses a Multi-Agent System and has the objective to help improve decision-making. Imagining that one organisation needs a service that can be provided by two other organisations, also present in the network, this part of the model is going to work towards helping the organisations choose what is the best choice, given the scenario and data available. This part of the model is also responsible to represent every organisation present in the network and when organisations negotiate or interact, this component is also going to handle the transaction and communicate the data to the first part of the model.A constante evolução de tecnologias atuais e a criação de novas tecnologias criou as condições necessárias para a existência de uma nova revolução industrial. Com a evolução de dispositivos móveis e com a chegada de novas tecnologias e ferramentas que começaram a ser introduzidas em ambiente industrial, como a impressão 3D, internet das coisas, inteligência artificial, realidade aumentada, entre outros, a industria conseguiu começar a explorar novas tecnologias e automatizar os seus processos de fabrico tradicionais, movendo as industrias para a quarta revolução industrial, conhecida por Industria 4.0. A adoção dos princípios da Indústria 4.0 levam as indústrias a evoluir os seus processos e a ter uma maior e melhor capacidade de produção, uma vez que as mesmas se vão tornar mais ágeis e introduzir melhorias nos seus ambientes de produção. Uma dessas melhorias na questão da interoperabilidade, com máquinas, sensores, dispositivos e pessoas a comunicarem entre si. A transparência da informação vai levar a uma melhor interpretação dos dados para efetuar decisões informadas, com os sistemas a recolher cada vez mais dados e informação dos diferentes pontos do processo de manufatura. (...

The Potential of Artificial Intelligence in Utilizing Circular Business Models : A Systematic Literature Review

Artificial intelligence is one of the fourth industrial revolution technologies that have been utilized in organizations. This research studies the potential benefits that artificial intelligence can provide to the organization in combination to circular economy. A concept of “sustainable industry 4.0” is introduced as the one concept that describes the sustainable dimension of industry 4.0 and combines circular economy and the technologies of industry 4.0. Focusing on the artificial intelligence benefits, especially in circular business models, provides the viewpoint of sustainability to artificial intelligence. Challenges and barriers to sustainable industry 4.0 and specially to utilizing artificial intelligence through circular economy and circular business models are presented. The research focuses on business-driven transition to circular business models from the linear model with the support of artificial intelligence. The aim of this research is to identify the potential of artificial intelligence and whether it provides the organization a competitive advantage. At the same time, providing knowledge of sustainable industry 4.0 and circular business models to ease the transition towards circularity for organizations. The research question of potential benefits provided by artificial intelligence technologies to the organization when transitioned to circular business models is answered by conducting a systematic literature review. From a total of 1634 articles, 11 papers were selected as primary study. The systematic literature review resulted in finding multiple benefits provided by artificial intelligence to organization while enhancing the transition to circular business models. Generally, the results provided a confirmation on how artificial intelligence can accelerate the transition to circularity through sustainable development goals and reciprocally sustainability provides a multifaceted platform for the artificial intelligence to work. Results presented how for example, artificial intelligence and machine learning algorithms supported decision making is the most prominent artificial technology for the organization to be beneficial. Besides the enhanced decision making, the results presented as benefits the flexibility of AI, which helps the organization to adapt to changes in the digital age as also the AI supported foundation for strategic development that leads to more sustainable business models. The results also presented drivers for organization to utilize artificial intelligence through circular business models. Such as savings and cost reductions, increased transparency and trust from consumers, and sustainable competitive advantage is seen as drivers for the organization to utilize artificial intelligence to achieve sustainable development goals.Tekoäly on yksi neljännen teollisen vallankumouksen teknologioista, joita on hyödynnetty organisaatioissa. Tämä tutkimus tutkii mahdollisia hyötyjä, joita tekoäly yhdistettynä kiertotalouteen voi tarjota organisaatiolle. Tutkimus esittele käsitteen "kestävä teollisuus 4.0", joka kuvaa teollisuus 4.0:n kestävää ulottuvuutta sekä yhdistää kiertotalouden ja teollisuus 4.0:n teknologiat. Keskittymällä erityisesti tekoälyn tuomiin etuihin kiertotalouden liiketoimintamalleissa, tutkimus tarjoaa kestävän näkökulman tekoälylle. Kestävän teollisuus 4.0:n ja erityisesti tekoälyn hyödyntämisen haasteita ja esteitä esitellään kiertotalouden ja kiertotalouden liiketoimintamallien kautta. Tutkimus keskittyy liiketoimintalähtöiseen siirtymiseen kiertotalouden liiketoimintamalleihin nykyisestä lineaarisesta talousmallista tekoälyn tuella. Tämän tutkimuksen tavoitteena on tunnistaa tekoälyn potentiaali ja todentaa tarjoaako se organisaatiolle kilpailuetua. Samalla tarjotaan tietoa kestävästä teollisuus 4.0:sta ja kiertotalouden liiketoimintamalleista helpottamaan organisaatioiden siirtymistä kiertotalouteen. Tutkimuskysymyksenä on: millaisia mahdollisia hyötyjä tekoäly voi antaa yritykselle siirryttäessä kiertotalouden liiketoimintamalleihin. Tutkimuskysymykseen vastataan systemaattisen kirjallisuuskatsauksen avulla. Yhteensä 1634 artikkelista valittiin 11 artikkelia ensisijaiseksi materiaaliksi (primary study). Systemaattisen kirjallisuuskatsauksen tuloksena löydettiin useita tekoälyn tarjoamia etuja organisaatiolle siirryttäessä kiertotalouden liiketoimintamalleihin. Yleisesti ottaen tulokset vahvistivat, kuinka tekoäly voi nopeuttaa siirtymistä kiertotalouteen kestävän kehityksen tavoitteiden kautta ja miten vastavuoroisesti kestävyys tarjoaa monipuolisen alustan tekoälylle toimia. Tulokset esittivät, kuinka esimerkiksi tekoälyn ja koneoppimisalgoritmien tukema päätöksenteko on merkittävin keinotekoinen teknologia organisaation hyödyksi. Tehostetun päätöksenteon lisäksi tulokset esittivät hyötyjä olevan muun muassa tekoälyn joustavuus, joka auttaa yritystä toimimaan digitaalisella aikakaudella muutoksiin sopeutuen sekä tekoälyn tukema perusta yrityksen strategiselle kehittämiselle kohti kestävämpiä liiketoimintamalleja. Tulokset esittelivät myös kannustimia organisaatiolle tekoälyn hyödyntämiseen kiertotalouden liiketoimintamallien kautta. Esimerkiksi säästöt ja kustannusten väheneminen, lisääntynyt läpinäkyvyys ja kuluttajien luottamus sekä kestävä kilpailuetu nähdään kannustimina organisaatiolle tekoälyn hyödyntämiseen kestävän kehityksen tavoitteiden saavuttamiseksi

Airline Ticket E-Reservation: Adoption Among Malaysians

Sistem tempahan tiket penerbangan telah banyak direvolusikan oleh syarikat-syarikat penerbangan melalui penggunaan Internet dan pengenalan alat-alat mudah alih moden. The air ticket reservation system has been much revolutionized by the airline companies through the usage of the Internet and introduction of modern mobile devices

A model for smart factories in the pharmaceutical manufacturing sector

Since the turn of the century, the manufacturing industry has metamorphosed from manually driven systems to digitalisation. Product life cycles have shortened and customer demands have become more intense. Globalisation has brought about challenges that drive the need for smart manufacturing. Industry 4.0 has emerged as a response to these demands. The integration of various processes, facilities and systems throughout the value chain and digitalisation of physical systems is promoted in Industry 4.0. Due to increased competitive pressures, organisations are strategically looking at automation to deliver competitive advantage in delivering products at the right cost, quality, time and volumes to the customers. Organisations are therefore looking for manufacturing solutions that are technology driven, such as cyber-physical systems, big data, collaborative robots and the Internet of Things. This allows autonomous communication throughout the value chain between machine-to-machine and human-to-machine. The smart factory, a component of Industry 4.0, is a self-organised, modular, highly flexible and reconfigurable factory that enables the production of customised products at low cost, therefore maximising profitability. Smart manufacturing can bring about competitive advantages for an organisation. Labour concerns have been raised against automation and smart manufacturing, citing potential job losses, workforce redundancy and potential employee lay-offs. This unease, in turn, influences the employees’ attitude towards technology, which could lead either to its acceptance or refusal. The purpose of this research is to enhance the understanding of smart factories in the pharmaceutical industry by conducting a systematic analysis of the factors which influence the attitude of those involved towards a smart factory implementation. This study focuses on the perceptions among employees and management. The research is a quantitative study consisting of a literature review of the key concepts related to Industry 4.0, smart factories and technology-acceptance theories. The empirical study consisted of surveys completed by management and employees of one of the pharmaceutical manufacturers in South Africa. The questionnaire used in this research consists of questions regarding demographic data and questions regarding the perception of change and factors influencing attitudes towards the acceptance of technology, within the pharmaceutical manufacturing company. Descriptive statistics were used to summarise the data into a more condensed form, which could simplify the identification of patterns in the data. Inferential statistics were used to validate if the conclusions made from the sample data could be inferred to a larger population. Various factors influence perceptions about ease of use and usefulness, which then, in turn, influence attitudes and the intention to use technology. These factors have been examined by numerous authors in the technology acceptance literature. Recommended factors based on the statistical analysis of the questionnaire results were identified. A model, supported by Exploratory Factor Analysis, Correlations and ANOVA Testing identified the following factors as having an influence on the Attitude towards the Positive Impact of Smart Factories, within the pharmaceutical manufacturing company: Training and Development, Individual Characteristics, Trust, Organisational Culture, Resources and Costs and Job Security. The importance of each factor was identified to understand its function how to improve the implementation of smart factories. The research results indicated that the perception of management and employees is different on factors like such as Training, Individual Characteristics, Trust, Resources and Costs, Automation and Support and Parent Company in relation to technology acceptance. There was however no difference in perception between managers and employees on Security, Government Laws and Regulations, Organisational Culture, Peer Support and Organisational Support in relation to technology acceptance. The research study contributed to the identification and understanding of the factors influencing the implementation of smart factories in the pharmaceutical industry

Effects of customer trust and online experiences in building hospitality brands

Customer trust embodies customer beliefs of actually receiving a promised service and manifestations of consumer’s confidences in an exchange parties reliability and integrity. The study is based on the fact as to how trusts criteria affect online purchase especially in regard to booking and buying the accommodations and also that accommodation providers assume that are very essential for consumers to make the online purchase. In total 150 consumers and 80 hotels owners/operators in India were examined. There are enormous discrepancies between consumers and accommodation providers were searched. Like formal guarantee of providers, security concern, refund of price paid delivery time and information about confirmation and they will switch from one brand to other due to promise breakage, less service quality, high price charged. However, these trust criteria were viewed inconsequential by the accommodation providers. It concluded with vast number of suggestions and recommendations for the accommodation providers need to include in their websites and build reputation and strong brands in the hospitality market

Employee acceptability of wearable mental workload monitoring in industry 4.0 : a pilot study on motivational and contextual framing

As Industry 4.0 will greatly challenge employee mental workload (MWL), research on objective wearable MWL-monitoring is in high demand. However, numerous research lines validating such technology might become redundant when employees eventually object to its implementation. In a pilot study, we manipulated two ways in which employees might perceive MWL-monitoring initiatives. We found that framing the technology in terms of serving intrinsic goals (e.g., improving health) together with an autonomy-supportive context (e.g., allowing discussion) yields higher user acceptability when compared to framing in terms of extrinsic goals (e.g., increasing productivity) together with a controlling context (e.g., mandating use). User acceptability still panned out neutral in case of the former, however - feeding into our own and suggested future work

Exploring the attributes of collaborative working in construction industry

Due to the increased level of uncertainty of construction market and the variety of building functions, the practitioners in construction need work together more closely, which means a higher degree of collaborative working is often necessary. There is evidence that higher degree of collaborative working can produce more successful projects, but there has been only limited research to examine the definition of collaborative working. The lack of understanding of collaborative working resulted in confusion of application of more collaborative approaches e.g. partnering or alliancing. The work presented here is part of an ongoing PhD study which aims to explore the impact of collaborative working on construction project performance. The aim of this paper is to identify a spectrum of attributes of collaborative working, which will facilitate the understanding what collaborative working is, why collaborative working is needed and how to work together. In order to identify those attributes of collaborative working, the method of ‘identification test’ will be adopted, which is based on the recent related literature

Evaluating the Customer Satisfaction’s Effect on Murabahah and Mudarabah Financing in Islamic Banking

There are a considerable number of studies on the service quality dimensions of banking industries, but little researches were carried out on the product quality dimensions, and this led to the minimal understanding of the impact of product quality dimensions from the customers’ standpoints, This research sought to identify the impact Islamic banking products (Murabahah and Mudarabah) dimensions on customer satisfaction. The study surveyed Islamic bank customers (users of the Islamic bank’s products in Nigeria) using questionnaires to seek responses, a convenient sampling technique was conducted to reach out to customers, and the use of PLS-SEM 3 was employed for the analysis of the data. The result model shows an R2 value of 0.414 (for Murabahah), which means 41% of the variance in customer satisfaction is explained by the exogenous constructs of perceived quality, cost, convenience and compliance of Murabahah, and R2 value of 0.309 (for Mudarabah) which means 31% of the variance in customer satisfaction is explained by the exogenous constructs of perceived quality, cost, convenience and compliance of Mudarabah. The values of R2 for Murabahah and Mudarabah show that the constructs were moderate in determining the satisfaction level of customers as they produced 0.414 and 0.309 respectively