Chinedu Onyeme and Kapila Liyanage
This study investigates the integration of Industry 4.0 (I4.0) technologies with condition-based maintenance (CBM) in upstream oil and gas (O&G) operations, focussing on…
Abstract
Purpose
This study investigates the integration of Industry 4.0 (I4.0) technologies with condition-based maintenance (CBM) in upstream oil and gas (O&G) operations, focussing on developing countries like Nigeria. The research identifies barriers to this integration and suggests solutions, intending to provide practical insights for improving operational efficiency in the O&G sector.
Design/methodology/approach
The study commenced with an exhaustive review of extant literature to identify existing barriers to I4.0 implementation and contextualise the study. Subsequent to this foundational step, primary data are gathered through the administration of carefully constructed questionnaires targeted at professionals specialised in maintenance within the upstream O&G sector. A semi-structured interview was also conducted to elicit more nuanced, contextual insights from these professionals. Analytically, the collected data were subjected to descriptive statistical methods for summarisation and interpretation with a measurement model to define the relationships between observed variables and latent construct. Moreover, the Relative Importance Index was utilised to systematically prioritise and rank the key barriers to I4.0 integration to CBM within the upstream O&G upstream sector.
Findings
The most ranked obstacles in integrating I4.0 technologies to the CBM strategy in the O&G industry are lack of budget and finance, limited engineering and technological resources, lack of support from executives and leaders of the organisations and lack of competence. Even though the journey of digitalisation has commenced in the O&G industry, there are limited studies in this area.
Originality/value
The study serves as both an academic cornerstone and a practical guide for the operational integration of I4.0 technologies within Nigeria's O&G upstream sector. Specifically, it provides an exhaustive analysis of the obstacles impeding effective incorporation into CBM practices. Additionally, the study contributes actionable insights for industry stakeholders to enhance overall performance and achieve key performance indices (KPIs).
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Chinedu Onyeme and Kapila Liyanage
The study aims to review the currently available Industry 4.0 (I4.0) maturity models (MMs) for manufacturing industries and analyse their applicability in the oil and gas (O&G…
Abstract
Purpose
The study aims to review the currently available Industry 4.0 (I4.0) maturity models (MMs) for manufacturing industries and analyse their applicability in the oil and gas (O&G) upstream sector. Knowing that the growth in demand for energy through crude oil and natural gas is still viable over the next decade, there is the drive to ensure sustenance and improvement in production. The study sees an opportunity in harnessing the gains of Industry 4.0 technologies for better solution-driven strategies in production processes, equipment availability and reliability which would translate into higher production performance. So, a review on the Industry 4.0 MMs is considered important.
Design/methodology/approach
A systematic and in-depth literature review was performed to identify the specific requirements of this industry. This study examined the key characteristics of the O&G upstream sector and identified research gaps that need to be addressed to successfully support this industry for Industry 4.0 implementation. An Industry 4.0 MM that reflects the industrial realities for this industry more accurately from insights drawn from reviews of existing MMs is proposed
Findings
The review of 19 selected Industry 4.0 MMs revealed that the existing MMs are not a direct fit for the O&G upstream industry. Only a few of the models were clear on validation but with subjectivity, low number of persons and industries involved as limitations; none of the models confirmed validation with the O&G industry. There are varying views on the model dimensions and maturity levels by each author and not all required areas specific to the O&G industries were acknowledged by the models. An MM specific to this industry is therefore required.
Originality/value
Although the journey of digitisation has commenced in the O&G industry, a reduction with the challenges of transition towards Industry 4.0 implementation and provision of support for improved efficiency is assured using a robust MM, as proposed in this paper.
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Terrence Perera and Kapila Liyanage
In recent years, computer simulation has become a mainstream decision support tool in manufacturing industry. In order to maximise the benefits of using simulation within…
Abstract
In recent years, computer simulation has become a mainstream decision support tool in manufacturing industry. In order to maximise the benefits of using simulation within businesses simulation models should be designed, developed and deployed in a shorter time span. A number of factors, such as excessive model details, inefficient data collection, lengthy model documentation and poorly planned experiments, increase the overall lead time of simulation projects. Among these factors, input data modelling is seen as a major obstacle. Input data identification, collection, validation, and analysis, typically take more than one‐third of project time. This paper presents a IDEF (Integrated computer‐aided manufacturing DEFinition) based approach to accelerate identification and collection of input data. The use of the methodology is presented through its application in batch manufacturing environments. A functional module library and a reference data model, both developed using the IDEF family of constructs, are the core elements of the methodology. The paper also identifies the major causes behind the inefficient collection of data.