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Article
Publication date: 1 June 2004

R.H. Khatibi, R. Lincoln, D. Jackson, S. Surendran, C. Whitlow and J. Schellekens

With the diversification of modelling activities encouraged by versatile modelling tools, handling their datasets has become a formidable problem. A further impetus stems…

Abstract

With the diversification of modelling activities encouraged by versatile modelling tools, handling their datasets has become a formidable problem. A further impetus stems from the emergence of the real‐time forecasting culture, transforming data embedded in computer programs of one‐off modelling activities of the 1970s‐1980s into dataset assets, an important feature of modelling since the 1990s, where modelling has emerged as a practice with a pivotal role to data transactions. The scope for data is now vast but in legacy data management practices datasets are fragmented, not transparent outside their native software systems, and normally “monolithic”. Emerging initiatives on published interfaces will make datasets transparent outside their native systems but will not solve the fragmentation and monolithic problems. These problems signify a lack of science base in data management and as such it is necessary to unravel inherent generic structures in data. This paper outlines root causes for these problems and presents a tentative solution referred to as “systemic data management”, which is capable of solving the above problems through the assemblage of packaged data. Categorisation is presented as a packaging methodology and the various sources contributing to the generic structure of data are outlined, e.g. modelling techniques, modelling problems, application areas and application problems. The opportunities offered by systemic data management include: promoting transparency among datasets of different software systems; exploiting inherent synergies within data; and treating data as assets with a long‐term view on reuse of these assets in an integrated capability.

Details

Management of Environmental Quality: An International Journal, vol. 15 no. 3
Type: Research Article
ISSN: 1477-7835

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Book part
Publication date: 26 August 2010

Sergio Biggemann

This paper reports the results of a three-year-long research on business relationships, relying on qualitative data gathered through multiple-case study research of four…

Abstract

This paper reports the results of a three-year-long research on business relationships, relying on qualitative data gathered through multiple-case study research of four focal companies operating in Australia. The industry settings are as follows: steel construction, vegetable oils trading, aluminum and steel can manufacture, and imaging solutions. The research analyzes two main aspects of relationships: structure and process. This paper deals with structure describing it by the most desired features of intercompany relationships for each focal company. The primary research data have been coded drawing on extant research into business relationships. The main outcome of this part of the research is a five construct model composed by trust, commitment, bonds, distance, and information sharing that accounts for all informants’ utterances about relationship structure.

Details

Organizational Culture, Business-to-Business Relationships, and Interfirm Networks
Type: Book
ISBN: 978-0-85724-306-5

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Article
Publication date: 3 August 2015

David Charles Robinson, David Adrian Sanders and Ebrahim Mazharsolook

This paper aims to describe the creation of innovative and intelligent systems to optimise energy efficiency in manufacturing. The systems monitor energy consumption using…

Abstract

Purpose

This paper aims to describe the creation of innovative and intelligent systems to optimise energy efficiency in manufacturing. The systems monitor energy consumption using ambient intelligence (AmI) and knowledge management (KM) technologies. Together they create a decision support system as an innovative add-on to currently used energy management systems.

Design/methodology/approach

Energy consumption data (ECD) are processed within a service-oriented architecture-based platform. The platform provides condition-based energy consumption warning, online diagnostics of energy-related problems, support to manufacturing process lines installation and ramp-up phase and continuous improvement/optimisation of energy efficiency. The systems monitor energy consumption using AmI and KM technologies. Together they create a decision support system as an innovative add-on to currently used energy management systems.

Findings

The systems produce an improvement in energy efficiency in manufacturing small- and medium-sized enterprises (SMEs). The systems provide more comprehensive information about energy use and some knowledge-based support.

Research limitations/implications

Prototype systems were trialled in a manufacturing company that produces mooring chains for the offshore oil and gas industry, an energy intensive manufacturing operation. The paper describes a case study involving energy-intensive processes that addressed different manufacturing concepts and involved the manufacture of mooring chains for offshore platforms. The system was developed to support online detection of energy efficiency problems.

Practical implications

Energy efficiency can be optimised in assembly and manufacturing processes. The systems produce an improvement in energy efficiency in manufacturing SMEs. The systems provide more comprehensive information about energy use and some knowledge-based support.

Social implications

This research addresses two of the most critical problems in energy management in industrial production technologies: how to efficiently and promptly acquire and provide information online for optimising energy consumption and how to effectively use such knowledge to support decision making.

Originality/value

This research was inspired by the need for industry to have effective tools for energy efficiency, and that opportunities for industry to take up energy efficiency measures are mostly not carried out. The research combined AmI and KM technologies and involved new uses of sensors, including wireless intelligent sensor networks, to measure environment parameters and conditions as well as to process performance and behaviour aspects, such as material flow using smart tags in highly flexible manufacturing or temperature distribution over machines. The information obtained could be correlated with standard ECD to monitor energy efficiency and identify problems. The new approach can provide effective ways to collect more information to give a new insight into energy consumption within a manufacturing system.

Details

Assembly Automation, vol. 35 no. 3
Type: Research Article
ISSN: 0144-5154

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Article
Publication date: 11 May 2021

Elizaveta Gavrikova, Irina Volkova and Yegor Burda

The purpose of this paper is to design a framework for asset data management in power companies. The authors consider asset data management from a strategic perspective…

Abstract

Purpose

The purpose of this paper is to design a framework for asset data management in power companies. The authors consider asset data management from a strategic perspective, linking operational-level data with corporate strategy and taking into account the organizational context and stakeholder expectations.

Design/methodology/approach

The authors conducted a multiple case study based on a literature review and three series of in-depth interviews with experts from three Russian electric power companies.

Findings

The main challenge in asset data management for electric power companies is the increasing amount and complexity of asset data, which is frequently incomplete or inaccurately collected, hard to translate to managerial language, focused primarily on the operational level. Such fragmented approach negatively affects strategic decision-making. The proposed framework introduces a holistic approach, provides context and accountability for decision-making and attributes data flows, roles and responsibilities to different management levels.

Research limitations/implications

The limitations of our study lie in the exploratory nature of case study research and limited generalization of the observed cases. However, the authors used multiple sources of evidence to ensure validity and generalization of the results. This article is a first step toward further understanding of the issues of transformation in power companies and other asset intensive businesses.

Originality/value

The novelty of the framework lies in the scope, focus and detailed treatment of asset data management in electric power companies.

Details

International Journal of Quality & Reliability Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0265-671X

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Article
Publication date: 25 November 2013

Sue Childs and Julie McLeod

The purpose of this paper is to complement a previous article on using the Cynefin framework to make sense of the electronic records management challenge. Its focus is on

Abstract

Purpose

The purpose of this paper is to complement a previous article on using the Cynefin framework to make sense of the electronic records management challenge. Its focus is on how to use Cynefin, and the ERM framework developed using it, as an approach to addressing this wicked problem. The aim is to provide examples of how they could be used in practice in different organisational contexts.

Design/methodology/approach

Four examples are provided. Empirical research data are used to underpin three of the examples and a thought experiment using published literature informs the fourth.

Findings

The examples illustrate the potential value and power of the Cynefin framework as both a practical and conceptual tool in the ERM context. It can be used to address the ERM challenge in different ways: as a strategic approach taking a holistic view and/or as a tactical approach at a more specific granular level. It can be used to inform practice by helping practitioners choose the most appropriate approach dependent on the level of complexity of the issue they are addressing, whether that is for a specific issue, a project or initiative, for planning or for exploratory, sense-making purposes.

Research limitations/implications

The examples draw on one qualitative, empirical set of research data and one published use. Further experimentation and practical use are required; others are encouraged to use Cynefin to test the propositions and provide further examples.

Practical implications

The examples provided can be adopted and/or adapted by records professionals, both practitioners and/or academics, at strategic and tactical levels in different records contexts.

Originality/value

This paper provides examples of adopting a different approach to tackling the wicked problem of managing electronic records using the Cynefin framework as a new lens.

Details

Records Management Journal, vol. 23 no. 3
Type: Research Article
ISSN: 0956-5698

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Article
Publication date: 5 May 2021

Dumitru Roman, Neal Reeves, Esteban Gonzalez, Irene Celino, Shady Abd El Kader, Philip Turk, Ahmet Soylu, Oscar Corcho, Raquel Cedazo, Gloria Re Calegari, Damiano Scandolari and Elena Simperl

Citizen Science – public participation in scientific projects – is becoming a global practice engaging volunteer participants, often non-scientists, with scientific…

Abstract

Purpose

Citizen Science – public participation in scientific projects – is becoming a global practice engaging volunteer participants, often non-scientists, with scientific research. Citizen Science is facing major challenges, such as quality and consistency, to reap open the full potential of its outputs and outcomes, including data, software and results. In this context, the principles put forth by Data Science and Open Science domains are essential for alleviating these challenges, which have been addressed at length in these domains. The purpose of this study is to explore the extent to which Citizen Science initiatives capitalise on Data Science and Open Science principles.

Design/methodology/approach

The authors analysed 48 Citizen Science projects related to pollution and its effects. They compared each project against a set of Data Science and Open Science indicators, exploring how each project defines, collects, analyses and exploits data to present results and contribute to knowledge.

Findings

The results indicate several shortcomings with respect to commonly accepted Data Science principles, including lack of a clear definition of research problems and limited description of data management and analysis processes, and Open Science principles, including lack of the necessary contextual information for reusing project outcomes.

Originality/value

In the light of this analysis, the authors provide a set of guidelines and recommendations for better adoption of Data Science and Open Science principles in Citizen Science projects, and introduce a software tool to support this adoption, with a focus on preparation of data management plans in Citizen Science projects.

Details

Data Technologies and Applications, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2514-9288

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Article
Publication date: 17 March 2014

David Robinson, David Adrian Sanders and Ebrahim Mazharsolook

– This paper aims to describe research work to create an innovative, and intelligent solution for energy efficiency optimisation.

Abstract

Purpose

This paper aims to describe research work to create an innovative, and intelligent solution for energy efficiency optimisation.

Design/methodology/approach

A novel approach is taken to energy consumption monitoring by using ambient intelligence (AmI), extended data sets and knowledge management (KM) technologies. These are combined to create a decision support system as an innovative add-on to currently used energy management systems. Standard energy consumption data are complemented by information from AmI systems from both environment-ambient and process ambient sources and processed within a service-oriented-architecture-based platform. The new platform allows for building of different energy efficiency software services using measured and processed data. Four were selected for the system prototypes: condition-based energy consumption warning, online diagnostics of energy-related problems, support to manufacturing process lines installation and ramp-up phase, and continuous improvement/optimisation of energy efficiency.

Findings

An innovative and intelligent solution for energy efficiency optimisation is demonstrated in two typical manufacturing companies, within one case study. Energy efficiency is improved and the novel approach using AmI with KM technologies is shown to work well as an add-on to currently used energy management systems.

Research limitations/implications

The decision support systems are only at the prototype stage. These systems improved on existing energy management systems. The system functionalities have only been trialled in two manufacturing companies (the one case study is described).

Practical implications

A decision support system has been created as an innovative add-on to currently used energy management systems and energy efficiency software services are developed as the front end of the system. Energy efficiency is improved.

Originality/value

For the first time, research work has moved into industry to optimise energy efficiency using AmI, extended data sets and KM technologies. An AmI monitoring system for energy consumption is presented that is intended for use in manufacturing companies to provide comprehensive information about energy use, and knowledge-based support for improvements in energy efficiency. The services interactively provide suggestions for appropriate actions for energy problem elimination and energy efficiency increase. The system functionalities were trialled in two typical manufacturing companies, within one case study described in the paper.

Details

Sensor Review, vol. 34 no. 2
Type: Research Article
ISSN: 0260-2288

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Article
Publication date: 1 December 1994

Gerti Kappel and Stefan Vieweg

Changes in market and production profiles require a more flexibleconcept in manufacturing. Computer integrated manufacturing (CIM)describes an integrative concept for…

Abstract

Changes in market and production profiles require a more flexible concept in manufacturing. Computer integrated manufacturing (CIM) describes an integrative concept for joining business and manufacturing islands. In this context, database technology is the key technology for implementing the CIM philosophy. However, CIM applications are more complex and thus more demanding than traditional database applications such as business and administrative applications. Systematically analyses the database requirements for CIM applications including business and manufacturing tasks. Special emphasis is given on integration requirements due to the distributed, partly isolated nature of CIM applications developed over the years. An illustrative sampling of current efforts in the database community to meet the challenge of non‐standard applications such as CIM is presented.

Details

Integrated Manufacturing Systems, vol. 5 no. 4/5
Type: Research Article
ISSN: 0957-6061

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Article
Publication date: 1 June 2004

Maura Ewa Merson, Lorena Montoya and Chris Paresi

This work aims at developing guidelines and methods for establishing urban hazard information infrastructure (UHII) for the City of Windhoek (CoW) in Namibia, to set up an…

Abstract

This work aims at developing guidelines and methods for establishing urban hazard information infrastructure (UHII) for the City of Windhoek (CoW) in Namibia, to set up an institutional and technical framework for spatial data exchange and sharing in development control and hazard management. An analysis of UHII requirements in the Twente Fire Brigades (The Netherlands) was first conducted and the Spatial Information Management Reference Model (RSIMM) was created. RSIMM was used as a reference to the Case‐Specific Spatial Information Management Model (CSIMM) for the CoW, where young institutions face financial, structural, legal and technical uncertainties. The new methodology to introduce UHII to the CoW was developed using combined soft and structured system development methods. The policies and strategies supporting UHII development were identified. The Urban Hazard and Emergency Management Information System (UHEMIS) development was chosen to initiate UHII introduction creating data and metadata management base for decision making in spatial development control, risk assessment and emergency response planning. The UHII and UHEMIS models are being designed next in this on‐going research.

Details

Management of Environmental Quality: An International Journal, vol. 15 no. 3
Type: Research Article
ISSN: 1477-7835

Keywords

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Article
Publication date: 10 June 2021

Álvaro Rodríguez-Sanz, Rosa Maria M. Arnaldo Valdes, Javier A. Pérez-Castán, Pablo López Cózar and Victor Fernando Gómez Comendador

Airports are limited in terms of capacity. Particularly, runways can only accommodate a certain number of movements (arrivals and departures) while ensuring safety and…

Abstract

Purpose

Airports are limited in terms of capacity. Particularly, runways can only accommodate a certain number of movements (arrivals and departures) while ensuring safety and determined operational requirements. In such a constrained operating environment, any reduction in system capacity results in major delays with significant costs for airlines and passengers. Therefore, the efficient operation of airports is a critical cornerstone for demand and delay management of the whole air transportation system. Runway scheduling deals with the sequencing of arriving and departing aircraft at airports such that a predefined objective is optimized subject to several operational constraints, like the dependency of separation on the leading and trailing aircraft type or the runway occupancy time. This study aims to develop a model that acts as a tactical runway scheduling methodology for reducing delays while managing runway usage.

Design/methodology/approach

By considering real airport performance data with scheduled and actual movements, as well as arrival/departure delays, this study presents a robust model together with an optimization algorithm, which incorporates the knowledge of uncertainty into the tactical operational step. The approach transforms the planning problem into an assignment problem with side constraints. The coupled landing/take-off problem is solved to optimality by exploiting a time-indexed (0, 1) formulation for the problem. The Binary Integer Linear Programming approach allows to include multi-criteria and multi-constraints levels and, even with some major simplifications, provides fewer sequence changes and target time updates, when compared to the usual approach in which the plan is simply updated in case of infeasibility. Thus, the use of robust optimization leads to a protection against tactical uncertainties, reduces delays and achieves more stable operations.

Findings

This model has been validated with real data from a large international European airport in different traffic scenarios. Results are compared to the actual sequencing of flights and show that the algorithm can significantly contribute to the reduction of delay, while adhering as much as possible to the operative procedures and constraints, and to the objectives of the airport stakeholders. Computational experiments performed on the case study illustrate the benefits of this arrival/departure integrated approach: the proposed algorithm significantly reduces weighted aircraft delay and computes efficient runway schedule solutions within a few seconds and with little computational effort. It can be adopted as a decision-making tool in the tactical stage. Furthermore, this study presents operational insights regarding demand and delay management based on the results of this work.

Originality/value

Scheduling arrivals and departures at runways is a complex problem that needs to address diverse and often competing considerations among involved flights. In the context of the Airport Collaborative Decision Making programme, airport operators and air navigation service providers require arrival and departure management tools that improve aircraft flows at airports. Airport runway optimization, as the main element that combines airside and groundside operations, is an ongoing challenge for air traffic management.

Details

Aircraft Engineering and Aerospace Technology, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1748-8842

Keywords

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