Search results

This paper aims to demonstrate the possibility of maintaining triple bottom line (TBL) sustainable performance in the petroleum industry via a case study. In particular, it presents the utilization of a lean-six-sigma (LSS) concept for investigating one of the underperforming support service activities in an engineering contractor (EC) and to indicate how LSS concepts enable the barriers to maintaining sustainable petroleum operations to be reduced for maintaining sustainable petroleum operations.

A case study has been carried out in an EC organization in relation to one of the support services (i.e. valves requisition process [VRP]) to demonstrate how LSS concepts enable the barriers to maintaining sustainable petroleum operations to be reduced for maintaining sustainable petroleum operations. Value stream mapping (VSM) and value stream analysis (VSA) have been utilized to investigate the barriers that inhibit sustainable operations. VSM and VSA have been performed to investigate the underperforming activities in the selected support service (i.e. VRP) using a current state map. After performing VSA, a future state map has been developed, indicating possible improvements in overall TBL sustainable performance.

VSM and VSA enable the barriers to maintaining TBL sustainable operations in the petroleum industry to be investigated, while minimizing waste in the ECs and asset owners’ organizations.

The study has been limited to ECs’ support services, which have been delivered based on asset operators’ requirements.

The suggested LSS approach and related analysis help practicing engineers to perform similar analysis for different engineering support services. Improved performance in support service results minimize health, safety and environmental challenges in asset operations, and the resulting waste reduction increases the return on investments.

Effective delivery of the assessments minimizes potential delays in projects related to petroleum operations, mitigating future accidents. It enhances the TBL sustainable performance of an asset-intensive industrial organization.

This manuscript addresses the inherent TBL sustainable performance challenges in the petroleum industry that have been caused by delayed projects. The responsibilities of projects’ delivery are mainly attributed to ECs. The EC organizations are operating in project mode, and projects delays are inherently caused by the frequently changing nature of: operators’ requirements; suppliers’ and/or manufacturers’ capabilities and restrictions; and lack of standardization in documentation and work processes (i.e. because of different engineering projects’ demands). Hence, this manuscript illustrates a methodology to demonstrate the possibility of TBL sustainable performance improvement in the petroleum industry via a case study (i.e. VRP-related project delivery performance improvement) in an EC organization utilizing the lean concept.

The purpose of this study is to investigate the integrated application of business process modeling and notation (BPMN) and value stream mapping (VSM) to improve knowledge work performance and productivity in police services. In order to explore the application of the hybrid BPMN-VSM approach in police services, this study uses the department of digital crime investigation (DCI) in one Norwegian police district as a case study.

Service process identification was the next step after selecting an appropriate organizational unit for the case study. BPMN-VSM-based current state mapping, including time and waste analyses, was used to determine cycle and lead time and identify value-adding and nonvalue-adding activities. Subsequently, improvement opportunities were identified, and the current state process was re-designed and constructed through future state mapping.

The study results indicate a 44.4% and 83.0% reduction in process cycle and lead time, respectively. This promising result suggests that the hybrid BPMN-VSM approach can support the visualization of bottlenecks and possible causes of increased lead times, followed by the systematic identification and proposals of avenues for future improvement and innovation to remedy the discovered inefficiencies in a complex knowledge-work environment.

This study focused on one department in a Norwegian police district. However, the experience gained can support researchers and practitioners in understanding lean implementation through an integrated BPMN and VSM model, offering a unique insight into the ability to investigate complex systems.

Complex knowledge work processes generally characterize police services due to a high number of activities, resources and stakeholder involvement. Implementing lean thinking in this context is significantly challenging, and the literature on this topic is limited. This study addresses the applicability of the hybrid BPMN-VSM approach in police services with an original public sector case study in Norway.

The purpose of this paper is to present a risk-based prioritization method (RBPM), using functional failure risk and strategic importance assessment, in order to support public managers' decision-making process for the planning and allocation of scarce resources.

The methodology incorporates two assessment matrices into a management group’s decision-making process for resource allocation. As part of an action research strategy, the authors present the developed RBPM and its application in one Norwegian police district.

The RBPM provides a processual approach to detect risk of failures in the organization, which can facilitate better planning and allocation of resources, to mitigate risks from materializing and enhance performance. The results also indicate that the proposed assessment models provide an easier approach to consolidating different perspectives and weighting the strategic importance of disciplinary functions, when prioritizing the planning and allocation of scarce resources is necessary.

The research is restricted in that it only considers one police district in Norway. Further limitation surrounds the issue of generalizability, as only one unit from the district is used. Further research should adapt and extend the developed RBPM in the district.

The RBPM may be of interest to public managers in the emergency sector operating with a large number of disciplinary functions in a highly dynamic and uncertain environment.

The RBPM applied in this study is based on approaches with advanced application in the oil and gas industry adapted to a contextually different environment which, in contrast, consists of functional hierarchies composed of human resources.

This study explores digital transformation in the tea supply chain within developing economies, with a focus on smallholder tea producers in Sri Lanka. Tea is one of the most widely consumed beverages in the world. Among the tea producers, smallholder tea producers account for a substantial portion of total tea production in several countries. Mobile phones play a significant role in providing smallholder producers with access to crucial agricultural information, markets and financial services.

This study adopts a deductive approach, analysing mobile phone ownership, literacy, experience and perception among smallholder tea producers. The chi-squared test of independence and hierarchical clustering methods were used to test the hypotheses and address the research questions.

The study identifies four clusters of smallholder tea producers as Basic Tech Adopters, Digital Laggards, Skeptical Feature Phone Users and Tech-savvy Adopters based on their characteristics towards mobile-based technologies. Approximately 75% of the surveyed sample, which included both tech-savvy and basic-tech adopters, showed a positive attitude toward adopting mobile-based agricultural technologies.

The study suggests developing targeted strategies and policies to enhance the productivity of the smallholder tea production process in developing economies. The study highlights the importance of awareness, access, affordability and availability when implementing digital services for businesses at the base of the pyramid, such as tea smallholdings in developing economies.

The present study aims to address the lack of data-driven empirical studies on the use of mobile phones in smallholder settings. The findings of this study enable the enhancement of entrepreneurship within the tea production supply chain, especially, within stakeholders who deliver digital transformation support services.

Corrosion loop development is an integral part of the risk-based inspection (RBI) methodology. The corrosion loop approach allows a group of piping to be analyzed simultaneously, thus reducing non-value adding activities by eliminating repetitive degradation mechanism assessment for piping with similar operational and design characteristics. However, the development of the corrosion loop requires rigorous process that involves a considerable amount of engineering man-hours. Moreover, corrosion loop development process is a type of knowledge-intensive work that involves engineering judgement and intuition, causing the output to have high variability. The purpose of this paper is to reduce the amount of time and output variability of corrosion loop development process by utilizing machine learning and group technology method.

To achieve the research objectives, k-means clustering and non-hierarchical classification model are utilized to construct an algorithm that allows automation and a more effective and efficient corrosion loop development process. A case study is provided to demonstrate the functionality and performance of the corrosion loop development algorithm on an actual piping data set.

The results show that corrosion loops generated by the algorithm have lower variability and higher coherence than corrosion loops produced by manual work. Additionally, the utilization of the algorithm simplifies the corrosion loop development workflow, which potentially reduces the amount of time required to complete the development. The application of corrosion loop development algorithm is expected to generate a “leaner” overall RBI assessment process.

Although the algorithm allows a part of corrosion loop development workflow to be automated, it is still deemed as necessary to allow the incorporation of the engineer’s expertise, experience and intuition into the algorithm outputs in order to capture tacit knowledge and refine insights generated by the algorithm intelligence.

This study shows that the advancement of Big Data analytics and artificial intelligence can promote the substitution of machines for human labors to conduct highly complex tasks requiring high qualifications and cognitive skills, including inspection and maintenance management area.

This paper discusses the novel way of developing a corrosion loop. The development of corrosion loop is an integral part of the RBI methodology, but it has less attention among scholars in inspection and maintenance-related subjects.

The calculation of quotations has been proven to be an extremely challenging matter in customized manufacturing requirements. There are significant wastages, which are attributed to activities related to the quotation preparation process (QPP) and their influence on an offer of delivery time to a customer. Hence, the purpose of this paper is to develop a tailor-made value stream mapping (VSM) approach, combined with a set of performance indicators for QPP performance measurement and management, to decrease the lead time of QPP.

Current and future state value stream maps have been developed to measure the performance of QPP. To minimize the weaknesses of the cycle efficiency indicator, additional indicators, assessing improvements to value- and non-value-added activities, external interested parties’ influence on lead time, etc., have been developed for QPP performance management. To illustrate the usefulness of the proposed indicators, a case study has been performed.

Only when all appropriate indicators are calculated than we have the whole overview of the current and future state in a QPP.

The proposed indicators were used only in one case study. If they are used in different case studies from different companies and operating in different industries, it will be possible to discover whether the presented indicators are enough to fully understand the analyzed process.

The proposed methodology is ready to be used in industry practice.

The presented VSM methodology, combined with a set of performance indicators for QPP, provides the originality of the work.

This paper aims to propose a methodology to support public managers' adaptation of the Hoshin Kanri (HK) strategy deployment approach in the context of lean thinking (LT), considering strategic alignment and consensus reaching when prioritizing a vital few of the organization's continuous improvement (CI) projects.

The methodology incorporates the A3 problem-solving report into the HK approach to identify and outline CI projects. The priority and deployment of the projects are weighted by a composite score for impact and innovation using the Delphi method. The proposed methodology was applied in one Norwegian police district as part of action research.

The obtained results indicate that the proposed methodology provides an intuitive and systematic approach to weigh the importance and ensure alignment of CI projects with the organization's strategy and goals. Consequently, this minimizes the possibility of strategy deployment priorities being weighted by decision bias and siloed decision-making.

The literature on strategy deployment in the context of LT in police services is significantly limited and this study aids in fixing this gap. The adapted HK approach can support the implementation of LT as an integral part of a comprehensive strategic management system, thereby enabling knowledge sharing and exploration of the extendibility of implemented best practices and improvement ideas to problems arising across the organization.

A systematic literature review is performed to reveal the state-of-the-art in the implementation of lean principles in the petroleum industry. This paper aims to generate a conceptual framework and reveal research gaps with respect to lean concept application in the petroleum industry.

After formulating research questions, the search strategy is generated, followed by data extraction, literature review and synthesis of the results. The search covers any studies in peer-reviewed scientific journals and conference proceedings in the period 1990-2017 that discuss the implementation of the lean concept in the petroleum industry.

The lean concept has been used to improve operational and technical aspects, contractor/supplier relationships, team organization and project management practice in the petroleum industry. Based on the literature review, a conceptual framework is generated comprising four main elements: leadership and commitment from management, employee involvement, cooperation and trust with contractors/suppliers and lean project management. These elements are the pillars that are founded on lean philosophy and principles to support technical/operational improvement in the organization. The types of literature identified indicate that the subject of the study is still immature.

This study focuses only on the upstream sector of the petroleum industry, which restricts the generalizability of the results to midstream and downstream businesses.

This paper provides knowledge and information regarding the current state of lean implementation in the petroleum industry. The developed conceptual framework provides general guidance for practitioners regarding lean implementation in the petroleum industry, and is also expected to support research on theory building.

Few studies have discussed the application of the lean concept in the petroleum industry. This paper contributes a platform for researchers and practitioners to comprehend how the lean concept has been applied in the petroleum industry, and provides a foundation for further studies on lean implementation in the petroleum industry.

This paper aims to explore knowledge work waste and defines the priorities for enhancing performance and productivity in policing and prosecution services (PPS), especially in the crime investigation process (CIP).

Using the analytic hierarchy process (AHP), a case study of a Norwegian police district is examined to identify and prioritize the most performance-vulnerable crime investigation unit, using the adapted knowledge work waste as the performance metric.

Nine waste categories and 15 subcategories are identified and understood within a two-dimensional network of managerial and operational waste adapted for the PPS. The AHP helps classify levels of priority for each knowledge work waste and orderly prioritization of crime investigation units.

The findings have limited generalizability, as they are based on a single Norwegian police district. This warrants research on the wider applicability of the adapted waste categories and approach.

This study can support public managers in implementing lean thinking and identifying the most prominent wastes in a complex system. In this context, processes and operations are among the factors dominated by knowledge work and are dependent on multiple stakeholders, cross-functional activities and interdisciplinary collaboration, which is more challenging to measure systematically and quantitatively than in a manufacturing environment.

This study contributes to the gap in lean thinking literature by advancing the knowledge on the adaptation and application of the foundational principles of lean thinking in the PPS and CIP.

The purpose of this paper is to focus on developing a knowledge-based engineering (KBE) approach to recycle the knowledge accrued in an industrial organization for the mitigation of unwanted events due to human error. The recycling of the accrued knowledge is vital in mitigating the variance present at different levels of engineering applications, evaluations and assessments in assuring systems’ safety. The approach is illustrated in relation to subsea systems’ functional failure risk (FFR) analysis.

A fuzzy expert system (FES)-based approach has been proposed to facilitate FFR assessment and to make knowledge recycling possible via a rule base and membership functions (MFs). The MFs have been developed based on the experts’ knowledge, data, information, and on their insights into the selected subsea system. The rule base has been developed to fulfill requirements and guidelines specified in DNV standard DNV-RP-F116 and NORSOK standard Z-008.

It is possible to use the FES-based KBE approach to make FFR assessments of the equipment installed in a subsea system, focussing on potential functional failures and related consequences. It is possible to integrate the aforementioned approach in an engineering service provider’s existing structured information management system or in the computerized maintenance management system (CMMS) available in an asset owner’s industrial organization.

The FES-based KBE approach provides a consistent way to incorporate actual circumstances at the boundary of the input ranges or at the levels of linguistic data and risk categories. It minimizes the variations present in the assessments.

The FES-based KBE approach has been demonstrated in relation to the requirements and guidelines specified in DNV standard DNV-RP-F116 and NORSOK standard Z-008. The suggested KBE-based FES that has been utilized for FFR assessment allows the relevant quantitative and qualitative data (or information) related to equipment installed in subsea systems to be employed in a coherent manner with less variability, while improving the quality of inspection and maintenance recommendations.