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Article
Publication date: 14 November 2023

Hajar Pouran Manjily, Mahmood Alborzi, Turaj Behrouz and Seyed Mohammad Seyed- Hosseini

This study aims to focused on conducting a comprehensive assessment of the technology readiness level (TRL) of Iran’s oil field intelligence compared to other countries with…

Abstract

Purpose

This study aims to focused on conducting a comprehensive assessment of the technology readiness level (TRL) of Iran’s oil field intelligence compared to other countries with similar oil reservoirs. The ultimate objective is to optimize oil extraction from this field by leveraging intelligent technology. Incorporating intelligent technology in oil fields can significantly simplify operations, especially in challenging-to-access areas and increase oil production, thereby generating higher income and profits for the field owner.

Design/methodology/approach

This study evaluates the level of maturity of present oil field technologies from the perspective of an intelligent oil field by using criteria for measuring the readiness of technologies. A questionnaire was designed and distributed to 18 competent oil industry professionals. Using weighted criteria, a mean estimate of oil field technical maturity was derived from the responses of respondents. Researchers evaluated the level of technological readiness for Brunei, Kuwait and Saudi Arabia’s oil fields using scientific studies.

Findings

None of the respondents believe that the intelligent oil field in Iran is highly developed and has a TRL 9 readiness level. The bulk of experts believed that intelligent technologies in the Iran oil industry have only reached TRL 2 and 1, or are merely in the transfer phase of fundamental and applied research. Clearly, Brunei, Kuwait and Saudi Arabia have the most developed oil fields in the world. In Iran, academics and executive and contracting firms in the field of intelligent oil fields are working to intelligently develop young oil fields.

Originality/value

This study explores the level of maturity of intelligent technology in one of Iran’s oil fields. It compares it to the level of maturity of intelligent technology in several other intelligent oil fields throughout the globe. Increasing intelligent oil fields TRL enables better reservoir management and causes more profit and oil recovery.

Details

Journal of Science and Technology Policy Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2053-4620

Keywords

Article
Publication date: 3 July 2017

Morteza Mahmoudzadeh and Mahmood Alborzi

Iran Nanotechnology Initiative Council could significantly increase the production of scientific articles in the field by imposing ten-year incentive policies so that Iran ranked…

Abstract

Purpose

Iran Nanotechnology Initiative Council could significantly increase the production of scientific articles in the field by imposing ten-year incentive policies so that Iran ranked 7 in this area in the year 2015. But this progress was insufficient to speed up the production and commercialization of nanotechnology products and Iran ranked 44 with a share of 0.03 per cent of nanotechnology production in the world. Therefore, Iran Nanotechnology Initiative Council as a governmental policymaker institution in this area has sought for the policy threefold increase of funding to speed up the production and commercialization of products in this field. But given that the result was not so clear, this research was formed in the form of modeling Iran Nanotechnology Innovation Network and testing various scenarios to increase its efficiency.

Design/methodology/approach

This paper uses simulation framework of innovation networks (SKIN) in an attempt to model the production innovation network in Iran in the field of nanotechnology that can measure the effect of incentive policies in changing the network structure and, consequently, increasing the level and pace of innovation in it. Given that the volume of articles produced in Iranian universities in the field of Nanotechnology had a high speed and volume in comparison with the volume of technical knowledge produced by companies, and because the SKIN framework did not consider the distinction between the two, in the first step, the framework is developed using the model of absorptive capacity of knowledge provided by Cohen and Levinthal (1990) and then the developed model was used to model the Innovation Network.

Findings

Finally, two policies of threefold increase of budget (Scenario 1) and increasing the support for joint projects (with maintaining the current budget level) (Scenario 2) were tested in this model. The social network analysis method was used to analyze the results of the two scenarios, where innovation network topology was compared (as an index to measure the network efficiency) in three states of current status of the network (the baseline scenario), implementing the first and second scenarios of extraction and with each other.

Originality/value

This paper models Iranian Nanotechnology Innovation Network for studying the evolution of the network as a result of executing different supportive scenarios.

Details

Journal of Science and Technology Policy Management, vol. 8 no. 2
Type: Research Article
ISSN: 2053-4620

Keywords

Article
Publication date: 16 August 2013

Sohrab Khalili Shavarini, Hossain Salimian, Jamshid Nazemi and Mahmood Alborzi

The purpose of this paper here is to present an operational model that establishes the necessary relationship between business strategy and operations strategy. Accordingly…

11588

Abstract

Purpose

The purpose of this paper here is to present an operational model that establishes the necessary relationship between business strategy and operations strategy. Accordingly, managers are enabled to define strategic business elements in the operations unit and align it with the business strategies.

Design/methodology/approach

Data were collected from 160 companies using a combination of structured interviews and closed questionnaire. In developing the alignment model, descriptive‐survey and correlation methods were used. For selecting the codes and types of alignments, a heuristic data analysis method was developed and applied.

Findings

This paper concludes that alignment is significantly different in successful and unsuccessful companies. Considering their performance, 25 alignment types have been identified out of which seven types have been found appropriate for the case.

Practical implications

The recommended model here is easy to use and helps managers to improve the performance of their companies by aligning their operation strategy with business strategy.

Originality/value

This paper presents a model that includes the content and process of operations strategy, using top‐down and resource‐based approaches. This model associates alignment with organizations performance, a subject that has been considered as one of the major and challenging issues in the strategic management efforts. Overall, a new and innovative model has been proposed here for building a vertical alignment between the strategies of the firm. The proposed alignment comes in two different levels.

Details

International Journal of Operations & Production Management, vol. 33 no. 9
Type: Research Article
ISSN: 0144-3577

Keywords

Article
Publication date: 12 October 2015

Mahmood Shafiee

Maintenance strategy selection (MSS) is considered as a complex multiple-criteria decision-making (MCDM) problem. The purpose of this paper is to present a comprehensive review on…

3251

Abstract

Purpose

Maintenance strategy selection (MSS) is considered as a complex multiple-criteria decision-making (MCDM) problem. The purpose of this paper is to present a comprehensive review on the use and application of MCDM approach and its associated case studies in the field of MSS.

Design/methodology/approach

The paper systematically classifies the published literature of both researchers and practitioners and then analyzes and reviews it methodically.

Findings

This paper outlines the important issues relevant to the subject, including the techniques used for data collection, the quantitative and qualitative criteria taken into account in decision making, the maintenance strategies considered for evaluation, the methods applied to find the solution, and the type of industries being studied. In each category, the gaps are identified along with recommendations for the future research work.

Practical implications

Literature on classification of the MCDM models used to select the most appropriate maintenance strategy is very limited. The proposed classification scheme not only will be useful to researchers, but also assists maintenance professionals to find the models that fit their specific needs.

Originality/value

The paper provides many references in the field, including the articles published in academic journals, conference papers, master and doctoral dissertations, text books, and industrial reports, and suggests a classification scheme according to various attributes.

Details

Journal of Quality in Maintenance Engineering, vol. 21 no. 4
Type: Research Article
ISSN: 1355-2511

Keywords

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