scholarly journals Industry 4.0 and Supply Chain Performance in the Oil and Gas Industry

2021 ◽  
Vol 9 (11) ◽  
pp. 2555-2560
Author(s):  
Akintokunbo, Oluwarotimi Odunayo ◽  
Idadokima, Samuel
Keyword(s):  
Supply Chain ◽  
Industry 4.0 ◽  
Communication Systems ◽  
Oil And Gas ◽  
Secondary Data ◽  
Oil And Gas Industry ◽  
Review Literature ◽  
Performance Measurement System ◽  
Supply Chain Performance ◽  
Exploratory Research

The purpose of this study is to investigate industry 4.0 and supply chain performance. Extant literature was reviewed. Secondary data such as E-books, journal articles projects were used. Exploratory research design was used for the study. Based on the review literature, it was revealed that, integrated supply chain performance measurement system (SCPMS) is paramount for an efficient supply chain management (SCM) at inter-organizational and beyond-the-boundary processes. The recent technological innovations (internet of things (IoTs), big data, and web-based communication systems) revamp the SCPMS through effective data collection, information sharing, and framework integration among the different SC partners across nations. The study recommend for further research on the obstacles facing industry 4.0 and supply chain performance in the oil and gas industries across nations.

scholarly journals Material Requirement Planning and Supply Chain Performance of Oil and Gas Firms in Rivers State, Nigeria

2021 ◽  
Vol 6 (2) ◽  
pp. 10-25
Author(s):  
Oluwarotimi Akintokunbo ◽  
Otonye Obom
Keyword(s):  
Supply Chain ◽  
Data Collection ◽  
Sample Size ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Supply Chain Performance ◽  
Material Requirement Planning ◽  
Material Requirement ◽  
Oil And Gas Firms ◽  
Rivers State

Purpose: This study examined the relationship between material requirement planning and supply chain performance of Oil and Gas firms in Rivers State, Nigeria. Methodology: The study adopted an explanatory research design with a causal type of investigation. Both primary and secondary methods of data collection were used to obtain relevant data for analysis. The instrument of data collection employed was the questionnaire. The study population comprised of two hundred and ninety-three (293) oil and gas servicing firms operating in Rivers State as enlisted in the Nigerian oil and gas industry annual report (2020). The sample size for the study comprised 149 oil and gas firms in Port Harcourt, Rivers state. The sample size was determined using the Taro Yamene formula. Furthermore, the researcher selected one management staff from each of the oil and gas firms operating in Rivers State as respondents for the study hence a total of one hundred and forty nine (149) respondents were used for the study. The data was analyzed using the Pearson’s Product Moment Correlation statistic through the aid of statistical packages for social science version 23.0. Findings: The result of the study revealed the existence of significant and positive relationship between material requirement planning and supply chain performance of oil and gas firms in Rivers State. Recommendation: The researcher concluded that material requirement planning affect supply chain performance of oil and gas firms in Rivers state and therefore recommended that managers of oil and gas firms should strategically manage their material and inventory processes in other to improve their supply chain performance.  

Implementing Cognitive Procurement and its Influence on Supply Chain During the Era of Digital Transformation in Oil and Gas Industry 4.0

2021 ◽  
Author(s):  
Manoj Kannankutty ◽  
Aditya Manoj Menon
Keyword(s):  
Supply Chain ◽  
Industry 4.0 ◽  
Online Survey ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Digital Transformation ◽  
Loop Model ◽  
Human Machine Interaction ◽  
Gas Industry ◽  
The Impact

Abstract The digital transformation is key for every oil and gas organization to implement its fourth industrial revolution (Industry 4.0). Digital transformation in procurement uses artificial intelligence, big data, market intelligence, etc. to create self-learning systems; for the procurement of goods and services. This is also known as cognitive procurement or procurement 4.0. The objective of this paper is to examine the methods of implementing cognitive procurement, the impact it creates in the procurement life cycle, and in the supply chain. The paper also provides insight into three governance models of human-machine interaction that is implemented in stages based on procurement requirement and technology adoption maturity of the organization.Human-in-the-loop modelHuman on-the-loop modelHuman out-of-loop model The data for this study is obtained by preparing a list of relevant questions from multiple sources. An online survey questionnaire is sent to the procurement professionals in different organizations in the oil and gas industry. The questions reveal procurement expert's responses for:Potential challenges for the digital transformation in procurement and supply chain.Methods of enabling technologies to leverage procurement procedures and processes. The results and the observations of the study are used to measure the benefits of implementing cognitive procurement in the oil and gas industry 4.0. The new transformed roles of procurement for industry 4.0 are also discussed in the conclusion, which includes:Daily activitiesProcurement decision-making activitiesStrategic SourcingProcurement to drive organizational profitability, effectiveness and efficiency The paper will benefit oil and gas organizations that are planning to implement cognitive procurement as part of the digital transformation. The paper will also benefit any parties interested in understanding more about cognitive procurement.

Blockchain and 6G-Based Supply Chain Management Framework for Oil and Gas Shipment

2021 ◽  
Author(s):  
Md Abdur Rahman ◽  
Syed M. Belal
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Oil And Gas ◽  
Current System ◽  
Oil And Gas Industry ◽  
Chain Process ◽  
Chain Management ◽  
It Systems ◽  
Supply Chain Management System ◽  
Gas Supply

Abstract Keeping track of the oil and gas supply chain is challenging task as the route and transportation requires sophisticated security environment - both physical systems’ and IT systems’ security. Thanks to the recent advancement in IoT, specialized sensors can keep track of the required supply chain environment. With the help of blockchain, the supply chain data can be immutably saved for further sharing with stakeholders. Due to the introduction of AI as an embedded element within 6G networks, the end-to-end supply chain process can now be automated for safety, security, and efficiency purposes. By leveraging 6G, AI, blockchain, and IoT, the supply chain data during the transportation or at rest can be monitored for any changed environment during the movement of the ship through national or international routes. In this paper, we study the requirements of such intelligent and secure supply chain management system conducive to the oil and gas industry. We also show our proof-of-concept implementation and initial test results. Our obtained results show promising prospect of the current system to be deployed to safeguard the oil and gas supply chain.

Applying Industry 4.0 technologies in the COVID–19 sustainable chains

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Carina Acioli ◽  
Annibal Scavarda ◽  
Augusto Reis
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Industry 4.0 ◽  
Supply Chain Performance ◽  
Chain Process ◽  
Sustainable Supply Chain ◽  
Content Type ◽  
Sustainable Performance ◽  
The Social ◽  
New Research

PurposeThe purpose of this paper is 1) to investigate the effects on the crucial Industry 4.0 technological innovations that interact between the real and virtual worlds and that are applied in the sustainable supply chain process; 2) to contribute to the identification of the opportunities, the challenges and the gaps that will support the new research study developments and 3) to analyze the impact of the Industry 4.0 technologies as facilitators of the sustainable supply chain performance in the midst of the Coronavirus (COVID-19).Design/methodology/approachThis research is performed through a bibliographic review in the electronic databases of the Emerald Insight, the Scopus and the Web of Science, considering the main scientific publications on the subject.FindingsThe bibliographic search results in 526 articles, followed by two sequential filters for deleting the duplicate articles (resulting in 487 articles) and for selecting the most relevant articles (resulting in 150 articles).Practical implicationsThis article identifies the opportunities and the challenges focused on the emerging Industry 4.0 theme. The opportunities can contribute to the sustainable performance of the supply chains and their territories. The Industry 4.0 can also generate challenges like the social inequalities related to the position of the man in the labor market by replacing the human workforce with the machines. Therefore, the man-machine relationship in the Industry 4.0 era is analyzed as a gap in the literature. Therefore, as a way to fill this gap, the authors of this article suggest the exploration of the research focused on the Society 5.0. Also known as “super-smart society,” this recent theme appeared in Japan in April 2016. According to Fukuda (2020), in addition to the focus on the technological development, the Society 5.0 also aims at the quality of life and the social challenge resolutions.Originality/valueThis article contributes to the analysis of the Industry 4.0 technologies as facilitators in the sustainable supply chain performance. It addresses the impacts of the Industry 4.0 technologies applied to the supply chains in the midst of the COVID-19 pandemic, and it analyzes the research gaps and limitations found in the literature. The result of this study can add value and stimulate new research studies related to the application of the Industry 4.0 technologies as facilitators in the supply chain sustainable performance. It can encourage the studies related to the COVID-19 impacts on the sustainable supply chains, and it can promote the research development on the relationship among the man, the machine and the labor in the Fourth Industrial Revolution.

scholarly journals An empirical study of oil and gas value chain agility in the UAE

2018 ◽  
Vol 25 (9) ◽  
pp. 3541-3569 ◽  
Author(s):  
Ala Shqairat ◽  
Balan Sundarakani
Keyword(s):  
Supply Chain ◽  
United Arab Emirates ◽  
Value Chain ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Value Chains ◽  
Study Region ◽  
Content Type ◽  
Moderate Effect ◽  
The Impact

Purpose The purpose of this paper is to investigate the agility of oil and gas value chains in the United Arab Emirates (UAE) and to understand the impact of implementing supply disruption (SD) strategies, outsourcing strategies (OS) and management strategies (MS) on oil and gas value chain agility (VCA). The results can support the oil and gas industry across the UAE to build resilience in the value chain. Design/methodology/approach The research design consists of a comprehensive literature review, followed by questionnaire-based survey responses of 106 participants and comprehensive statistical analysis, thus validate the developed theoretical framework and contribute to both practical and methodological approaches. Findings The findings indicate that oil and gas value chain in the UAE has moderate a significant degree of SD, when OS in place that are synchronized with the overall MS. Among the hypotheses developed, two were accepted thus warranting both SD strategies (r=+0.432) and MS (r= +0.457) found to have a positive moderate effect on VCA. The third hypothesis was rejected by revealing OS (r=+0.387) found to have a positive moderate relationship with VCA. Therefore, implementation of all three strategies has a positive moderate effect on the agility of the value chain and, therefore, supports to sustain competitive position. Research limitations/implications Some of the limitations of this research include the geographic coverage of the study region and other methodological limitation. Practical implications The research provides guidance for oil and gas supply chain managers to better understand the critical factors that impact and determine VCA. The paper also describes relevant strategies that should be taken into consideration by these managers in order to build their agile value chains. Social implications The research contributes to the social dimensions of supply chain sustainability of how resilient is the oil and gas value chain during uncertain conditions, so that it can respond to uncertain changes in order to contribute to corporate social responsibility. Originality/value This research is the first of its kind in the UAE region to assess the link between dimensions of agile value chain, OS, SD strategies and MS primarily from the Emirates of Abu Dhabi and Dubai.

scholarly journals A Survey on Industry 4.0 for the Oil and Gas Industry: Upstream Sector

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Olakunle Elijah ◽  
Pang Ai Ling ◽  
Sharul Kamal Abdul Rahim ◽  
Tan Kim Geok ◽  
Agus Arsad ◽  
...  
Keyword(s):  
Industry 4.0 ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Gas Industry

PLANNING OF SALES AND OPERATIONS (S&OP) AS A TOOL FOR OPTIMIZING THE PROCESS OF MATERIAL AND TECHNICAL SUPPORT OF THE OIL AND GAS COMPLEX

2021 ◽  
Vol 2 (1) ◽  
pp. 11-16
Author(s):  
Milena Vladimirovna Zagrebelskaya ◽  
Keyword(s):  
Supply Chain ◽  
Oil And Gas ◽  
Oil And Gas Industry ◽  
Technical Support ◽  
Integrated Planning ◽  
Gas Industry ◽  
Operations Planning ◽  
Information Logistics ◽  
Modern Information ◽  
Oil And Gas Enterprises

The article providesthe main problems of oil and gas enterprises in the supply chains in the loop of procurement based onexample of Uzbekneftegaz. The possibilities of modern information logistics technologies in solving the above problems are reflected. The author's model of integratedplanning based on the logistics technology Sales & Operations Planning, taking into account the peculiarities of the oil and gas industry, is proposed for implementation at oil and gas enterprises in order to improve the efficiency of the planning and implementation of business processes.Key Words:logistics, supply chain, sales and operations planning, S&OP, oil and gas complex, integrated planning

A Comprehensive Review of the Fourth Industrial Revolution IR 4.0 in Oil and Gas Industry

2021 ◽  
Author(s):  
Cenk Temizel ◽  
Celal Hakan Canbaz ◽  
Hakki Aydin ◽  
Bahar F. Hosgor ◽  
Deniz Yagmur Kayhan ◽  
...  
Keyword(s):  
Industry 4.0 ◽  
Industrial Revolution ◽  
Oil And Gas ◽  
Petroleum Industry ◽  
Oil And Gas Industry ◽  
Learning Technologies ◽  
Real Field ◽  
Gas Industry ◽  
History Of ◽  
History Of Use

Abstract Digital transformation is one of the most discussed themes across the globe. The disruptive potential arising from the joint deployment of IoT, robotics, AI and other advanced technologies is projected to be over $300 trillion over the next decade. With the advances and implementation of these technologies, they have become more widely-used in all aspects of oil and gas industry in several processes. Yet, as it is a relatively new area in petroleum industry with promising features, the industry overall is still trying to adapt to IR 4.0. This paper examines the value that Industry 4.0 brings to the oil and gas upstream industry. It delineates key Industry 4.0 solutions and analyzes their impact within this segment. A comprehensive literature review has been carried out to investigate the IR 4.0 concept's development from the beginning, the technologies it utilizes, types of technologies transferred from other industries with a longer history of use, robustness and applicability of these methods in oil and gas industry under current conditions and the incremental benefits they provide depending on the type of the field are addressed. Real field applications are illustrated with applications indifferent parts of the world with challenges, advantages and drawbacks discussed and summarized that lead to conclusions on the criteria of application of machine learning technologies.

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