scholarly journals Smart contracts in the Industry 4.0 innovation business processes

Logistics ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 14
Author(s):  
Athina G. Bright ◽  
Stavros T. Ponis

In the last decade, the Industry 4.0 concept has introduced automation and cyber-physical systems as the core elements of future logistics, supported by an array of technologies, such as augmented reality (AR) providing the necessary support for the digital transformation of manufacturing and logistics and the smartification and digital refinement of traditional pre-Industry 4.0 processes. This paper studies the influence and the potential of gamification techniques in supporting innovative Industry 4.0-enhanced processes in the contemporary warehouse work ecosystem. Gamification in the workplace aims to motivate the employees and increase their involvement in an activity, while at the same time creating a sense of an everyday different experience rather than a set of repetitive and monotonous tasks. Since the design of such a system is a complex process, the most widespread design frameworks are studied, and the emphasis is on the principal game elements and their connection to mobilization mechanisms. Finally, an initial proposal of a gamification framework to support the AR-enhanced order picking process in contemporary logistics centers is provided with an emphasis on the mechanics of a fair and functional reward system. The proposed approach aims to showcase the potential alignment of business processes to human motivation, respecting the differences between tasks and the workers’ cognitive workload.


2021 ◽  
Vol 18 ◽  
pp. 569-580
Author(s):  
Kateryna Kraus ◽  
Nataliia Kraus ◽  
Oleksandr Manzhura

The purpose of the research is to present the features of digitization of business processes in enterprises as a foundation on which the gradual formation of Industry 4.0 and the search for economic growth in new virtual reality, which has every chance to be a decisive step in implementing digital strategy for Ukraine and development of the innovation ecosystem. Key problems that arise during the digitalization of business processes in enterprises are presented, among which are: the historical orientation of production to mass, “running” sizes and large batches; large-scale production load; the complexity of cooperation and logic between production sites. It is determined that high-quality and effective tools of innovation-digital transformation in the conditions of virtual reality should include: a single system of on-line order management for all enterprises (application registration – technical expertise – planning – performance control – shipment); Smart Factory, Predictive Maintenance, IIoT, CRM, SCM. Features of digital transformation in the part of formation of enterprises of the ecosystem of Industry 4.0 are revealed. The capabilities and benefits of using Azure cloud platform in enterprises, which includes more than 200 products and cloud services, are analyzed. Azure is said to support open source technologies, so businesses have the ability to use tools and technologies they prefer and are more useful. After conducting a thorough analysis of the acceleration of deep digitalization of business processes by enterprises, authors proposed to put into practice Aruba solution for tracking contacts in the fight against COVID-19. Aruba technology helps locate, allowing you to implement flexible solutions based on Aruba Partner Ecosystem using a USB interface. It is proposed to use SYNTEGRA – a data integration service that provides interactive analytics and provides data models and dashboards in order to accelerate the modernization of data storage and management, optimize reporting in the company and obtain real-time analytics. The possibilities of using Azure cloud platform during the digitization of business processes of enterprises of the ecosystem of Industry 4.0 in the conditions of virtual reality are determined.


2022 ◽  
pp. 1-18
Author(s):  
Ilknur Taştan Boz ◽  
Özden Ibrahimağaoğlu

Industries have undergone three fundamental transformation processes that were revolutionary. Following these processes, industries have been confronted with the phenomenon of Industry 4.0, known as the 4th Industrial Revolution, that is acknowledged as a new transformation process. The basic dynamics of this phenomenon include smart robots, simulation, the internet of things, cloud, additive manufacturing, and big data. It is of utmost importance for businesses that are involved in this process, that are new and trying to adapt to the process, to be prepared and adapt to the effects of Industry 4.0 dynamics. These dynamics lead to significant developments in business models, business processes, organizational structures, employees, and human resource processes. When Industry 4.0 and its dynamics are evaluated in general, businesses that follow the process and make necessary managerial adjustments will be ahead of the competition.


Author(s):  
Megashnee Munsamy ◽  
Arnesh Telukdarie ◽  
Pavitra Dhamija

Logistics activities are significant energy consumers and known contributors to GHG emissions, hence optimisation of logistics energy demand is of critical importance. The onset of the fourth Industrial revolution delivers significant technological opportunities for logistics optimisation with additional benefits in logistics energy optimisation. This research propositions a business process centric logistics model based on Industry 4.0. A Logistics 4.0 architecture is developed comprising Industry 4.0 technologies and associated enablers. The Industry 4.0 architecture components are validated by conducting a Systematic Literature Review on Industry 4.0 and logistics. Applying the validated Logistics 4.0 architecture to a cyber physical logistics energy model, based on the digitalisation of business processes, a comprehensive simulation is developed identified as the Logistic 4.0 Energy Model. The model simulates the technological impact of Industry 4.0 on a logistics network. The model generates energy and CO2 emission values for “as-is” and “to-be” Industry 4.0 scenarios.


2019 ◽  
Vol 25 (7) ◽  
pp. 1867-1890 ◽  
Author(s):  
Megashnee Munsamy ◽  
Arnesh Telukdarie ◽  
Johannes Fresner

Purpose Sustainability is an accepted measure of business performance, with reductions in energy demand a commonly practised sustainability initiative by multinational corporations (MNCs). Traditional energy models have limited scope when applied to the entire MNC as the models exhibit high data and time intensity, high technical proficiency, specificity of application and omission of non-manufacturing activities. The purpose of this paper is to propose a process centric energy model (PCEM), which adopts a novel approach of applying business processes for business energy assessment and optimisation. Business processes are a fundamental requirement of MNCs across all sectors. The defining features of the proposed model are genericity, reproducibility, minimum user input data, reduced modelling time and energy evaluation of non-manufacturing activities. The approach forwards the adoption of Industry 4.0, a subset of which focuses on business process automation or part thereof. Design/methodology/approach A quantitative approach is applied in development of the PCEM. The methodology is demonstrated by application to the procure to pay and electroplating business processes. Findings The PCEM quantifies and optimises the business energy demand and associated carbon dioxide emissions of the procure to pay and electroplating business processes, validating the application of business processes. The application demonstrates minimum user inputs as only equipment operational parameters are required and minimum modelling time as business process models and optimisation options are pre-defined requiring only user modification. As MNCs have common business processes across multiple sites, once a business process energy demand is quantified, its inputs are applied as the default in the proceeding sites, only requiring updating. The model has no specialist skills requirement enabling business wide use and eliminating costs associated with training and expert’s services. The business processes applied in the evaluation are developed by the researchers and are not as comprehensive as those in actual MNCs, but is sufficiently detailed to accurately calculate an MNC energy demand. The model databases are not exhaustive of all resources found in MNCs. Originality/value This paper provides a new approach to MNC business energy assessment and optimisation. The model can be applied to MNEs across all sectors. The model allows the integration of manufacturing and non-manufacturing activities, as it occurs in practice, providing holistic business energy assessment and optimisation. The model analyses the impacts of the adoption of Industry 4.0 technologies on business energy demand, CO2 emission and personnel hours.


2020 ◽  
Vol 32 (23) ◽  
pp. 17361-17378
Author(s):  
Konstantinos Demertzis ◽  
Lazaros Iliadis ◽  
Nikos Tziritas ◽  
Panagiotis Kikiras

2020 ◽  
Vol 21 (4) ◽  
pp. 565-581 ◽  
Author(s):  
Elena G. Popkova ◽  
Bruno S. Sergi

PurposeThe purpose of this article is to determine the future proportion and variants of usage of human intellect and artificial intelligence (AI) in entrepreneurship of industry 4.0 that fits social entrepreneurship the most. It could be convergence (simultaneous utilization during the same entrepreneurial processes with the emphasis on unique features by the terms of the competition) or divergence (usage during different business processes by the terms of labor division).Design/methodology/approachThe authors determine the influence of usage of human capital and AI on the efficiency of social entrepreneurship. The authors identify the perspective directions of usage of AI in social entrepreneurship and evaluate the readiness and interest in the implementation of these directions of concerned parties. The authors also model the optimal proportions and the variant of usage of human intellect and AI in social entrepreneurship in the conditions of Industry 4.0 in the future (until 2030).FindingsIt is found that social entrepreneurship will use the opportunities of Industry 4.0 for optimization of its activities until 2030, but will refuse from full automatization, using human intellect and AI at the same time.Originality/valueThe most perspective directions of application of AI at social companies are a collection of social goods and services, marketing studies and promotion of social goods and services. Neither convergence nor divergence of human and artificial intellectual capital does not fully conform to the interests of concerned parties. The most preferable (optimal) variant of usage of human intellect and AI in social entrepreneurship in the Industry 4.0 is human intelligent decision support.


2018 ◽  
Vol 6 (5) ◽  
pp. 48-55
Author(s):  
Кирилл Мельников ◽  
Kirill Melnikov

In this paper an integrated approach to a problem related to minimization of gas supplier’s reputation losses connected with accidents on a gas pipeline and disruption of gas delivery to a consumer with the help of smart contracts is stated. Nowadays analysts and methodologists of pipeline companies perform assessment of expected and actual material expenses at an accident on GTS objects. Account and analytics of reputation losses either isn’t conducted in all, or is implemented in the frame of separate business processes which aren’t integrated into processes of enterprise budget’s management and planning. Such situation is disconcertingly. In the era of globalization the cost of a company and its business reputation depends significantly on the attitude towards it in society. In Europe and USA the major oil and gas companies invest huge money in increasing of their positive image in the eyes of population. Any significant accident which has happened in unforeseen time and unsuccessful place can completely destroy reputation of any company. Modern corporate IT-decisions allow unite a number of data flows in the uniform analytical module now. Information collected in such modules in Gazprom PJSC helps to solve optimizing problems both within planning of material inputs, and within accounting of reputation expenses. In this work a theoretical model for assessment of reputation losses at an accident on a linear part of a gas transmission system (GTS) of Gazprom PJSC is given. Modern theoretical models for definition of function of supplier’s reputation losses have been used. The review of possible application for SAP decisions and Blockchain technology in current business processes of Gazprom JSC in the frame of the problem solution is given. For a clear understanding how to integrate this decision into existing business processes the graphic description of the decision work scheme is given. The principles of this approach can be applied not only in working processes of Gazprom PJSC, but also adapted according to other pipeline companies’ needs. Possible fast introduction of cryptoruble in Russia can offer new prospects for mass introduction of this tool in the context of smart contracts.


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