Javaneh Ramezani

ORCID: 0000-0003-1414-186X
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About
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Research Areas
  • Supply Chain Resilience and Risk Management
  • Digital Transformation in Industry
  • Collaboration in agile enterprises
  • Big Data and Business Intelligence
  • Industrial Vision Systems and Defect Detection
  • Sustainable Supply Chain Management
  • Blockchain Technology Applications and Security
  • Multi-Criteria Decision Making
  • Advanced Manufacturing and Logistics Optimization
  • Outsourcing and Supply Chain Management
  • Construction Project Management and Performance
  • Robot Manipulation and Learning
  • Mineral Processing and Grinding
  • Impact of AI and Big Data on Business and Society
  • Advanced Statistical Process Monitoring
  • Fault Detection and Control Systems
  • Quality and Supply Management

University of Lisbon
2017-2022

Uninova
2019-2021

Universidade Nova de Lisboa
2017-2020

Imam Khomeini International University
2020

10.1016/j.techfore.2019.119846 article EN Technological Forecasting and Social Change 2019-12-04

The notion of digital transformation encompasses the adoption and integration a variety new information communication technologies for development more efficient, flexible, agile, sustainable solutions industrial systems. Besides technology, this process also involves organizational forms leads to business models. As such, work addresses contribution collaborative networks such transformation. An analysis aspects required in various dimensions 4th revolution is conducted based on literature...

10.3390/app9245431 article EN cc-by Applied Sciences 2019-12-11

Industry 4.0 (I4.0) represents the Fourth Industrial Revolution in manufacturing, expressing digital transformation of industrial companies employing emerging technologies. Factories future will enjoy hybrid solutions, while quality is heart all manufacturing systems regardless type production and products. Quality a branch I4.0 with aim boosting by smart solutions intelligent algorithms. There are many conceptual frameworks models, main challenge to have experience action at workshop level....

10.3390/pr8060634 article EN Processes 2020-05-26

The notion of Industry 4.0 encompasses the adoption new information technologies that enable an enormous amount to be digitally collected, analyzed, and exploited in organizations make better decisions. Therefore, finding how can adopt big data (BD) components improve their performance becomes a relevant research area. This issue is becoming more pertinent for small medium enterprises (SMEs), especially developing countries encounter limited resources infrastructures. Due lack empirical...

10.3390/bdcc5040068 article EN cc-by Big Data and Cognitive Computing 2021-11-24

In recent years, the selection of a robot for particular industrial purposes is one most challenging problems in manufacturing environment based on automation and smartness real-time decision-making. At present, several types robots with various capabilities, features, facilities, specifications are available market. This makes decision-making process more complicated due to increase complexity, advanced technologies, features that continually being incorporated into by manufacturers. The...

10.1016/j.heliyon.2020.e03859 article EN cc-by Heliyon 2020-05-01

Evaluating organizational readiness for adopting new technologies always was an important issue managers. This complicated subjects such as Big Data is undeniable. Managers tend to adopt Data, with the best readiness. But this not possible unless they can assess their In present paper, we propose a model evaluate adoption. To accomplish objective, firstly, identified criteria that impact based on comprehensive literature review. next step using Principal Component Analysis (PCA) criterion...

10.15837/ijccc.2020.3.3874 article EN cc-by-nc International Journal of Computers Communications & Control 2020-04-21

Turbulence and unexpected disruptive events are showing with an increasing frequency growing impact, which represent major challenges for sustainability of businesses. Therefore, finding how organizations can strive even improve or gain benefits in environment scenarios became a relevant research area, resilience antifragility two significant approaches. This paper argues that collaboration business ecosystems is promising approach to cope disruptions. A brief overview existing strategies as...

10.1016/j.procs.2019.12.029 article EN Procedia Computer Science 2019-01-01

Abstract The notion of Industry 4.0 encompasses the adoption new information technologies that enable an enormous amount to be digitally collected, analysed, and exploited in organizations make better decisions. Therefore, finding how can adopt big data components improve their performance became a relevant research area. This issue is becoming more pertinent for SMEs. study investigates impact on SMEs by obtaining required from experts. quantitative investigation followed mixed approach,...

10.21203/rs.3.rs-66047/v1 preprint EN cc-by Research Square (Research Square) 2020-09-21

The increasing growth of information and communication technologies along with the extensive reliance today's organizations businesses on these have rendered decisions how to outsource implementation system (IS) as well technology (IT) projects. Besides, selection competent contractors for IS/IT projects is one most crucial issues which must deal. Therefore, numerous researchers conducted studies in this regard. However, because expanded intensive inter-organizational interactions inevitable...

10.1109/yef-ece.2019.8740829 article EN 2019-05-01

Multi-criteria decision-making (MCDM) methods have been implemented in many fields. In the meantime, several proposed to obtain weight of criteria determined by various different ways. this paper, a new approach, called simultaneous interpretive structural modelling and weighting (SISMW), is solve multi-criterion problem. Using SISMW, relationship between them could be simultaneously. like ISM method, pair comparison was made decision-maker determine relationships among criteria. With help...

10.37190/ord220106 article EN cc-by-nc-nd Badania Operacyjne i Decyzje/Operations Research and Decisions 2022-01-01
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