The Experts below are selected from a list of 7164 Experts worldwide ranked by ideXlab platform

Andreas Lindner - One of the best experts on this subject based on the ideXlab platform.

  • Development of a knowledge-based feedback assistance system of Product use information for Product improvement
    International Journal of Product Development, 2014
    Co-Authors: Susanne Dienst, Michael Abramovici, Madjid Fathi, Andreas Lindner
    Abstract:

    Due to technological advancement, an increase in creating and storing digital data can be observed today, for instance throughout the Product life cycle. Through especially Product use, a large number of data are created. The data are mainly used during the Product use phase (e.g. condition-based maintenance). However, those data can be used as feedback to generate knowledge and support the Product Developer through improving future Product generations. This paper presents development and prototypical realisation of a feedback assistance system for the management, analysis and visualisation of feedback data. The system supports a Product Developer by improving the process of decision-making to discover development potentials. Thereupon, four modules have been developed to analyse related indicators statistically and to diagnose machine failures. The obtained knowledge about the current condition of machines should then be deployed to improve the next machine generations utilising the modules for decision support and prediction.

  • Use Case of Providing Decision Support for Product Developers in Product Improvement Processes
    Integration of Practice-Oriented Knowledge Technology: Trends and Prospectives, 2013
    Co-Authors: Michael Abramovici, Andreas Lindner, Susanne Dienst
    Abstract:

    Industrial goods like pumps, engines, and gears are subject of cyclical improvements. An important input for such Product updates is information from the use phase, especially information about failures that occurred during the use of current Products. In a current research project the authors have developed a concept and a prototype for a Feedback Assistant System. The first realized modules of this assistant provide filtered and condensed Product use information to the Product Developer. The paper in hands presents an extended concept and use case to assist the Product Developer in choosing the most suitable alternative in Product improvement processes. The decisions are based on hard facts using diverse criteria.

  • Exploiting Service Data of Similar Product Items for the Development of Improved Product Generations by Using Smart Input Devices
    Lecture Notes in Production Engineering, 2013
    Co-Authors: Michael Abramovici, Andreas Krebs, Andreas Lindner
    Abstract:

    State-of-the-art industrial Products generate large amounts of data that is not lead back into Product development. The use of modern technologies like mobile devices and Auto-ID to identify Product items and collect data offers a new, rich data source that can be used by Product development. To gain an understanding of the Products in practical application, the collected data can be processed by assistant systems for the improvement of Products. The assistant system outlined in the paper in hand uses statistical methods and methods derived from risk management to provide a comprehensive analysis. A short overview of the analysis results is presented to the Product Developer as a preselection of parts worth improving. Based on the preselection, the Product Developer can choose specific parts and gain further information via the assistant system. The system itself provides that information using different methods of Product and information visualization.

  • concept for improving industrial goods via contextual knowledge provision
    International Conference on Knowledge Management and Knowledge Technologies, 2012
    Co-Authors: Susanne Dienst, André Klahold, Michael Abramovici, Madjid Fathi, Andreas Lindner
    Abstract:

    At present, Product lifecycle data is provided, used, and archived only for very specific purposes. Textual data generated in Product use can be very comprehensive and contain valuable information beyond its original purpose, e.g. for Product development or improvement. This kind of information, however, is not fed back systematically, as its evaluation is currently not possible due to a lack of suitable methods and tools in Product development. The paper in hand presents a concept designed to support Product Developers by introducing maintenance, service, and customer data, which has undergone restructuring into textual form in the Product use phase, into Product development. To process the restructured textual data, customized text mining methods are generated as a part of knowledge management in Product development. These methods aim at identifying Products, Product generations, and failure descriptions, as well as the relationships among them. The knowledge gained through text mining is visualized in the work environment familiar to the Product Developer, and implements utilitarian visualization methods. Visualization is integrated into existing IT systems and provides knowledge required for Product improvement or development in a target-oriented way. This extension to knowledge-based Product development facilitates more efficient improvement of current and future Products.

  • A conceptual data management model of a feedback assistance system to support Product improvement
    2011 IEEE International Conference on Systems Man and Cybernetics, 2011
    Co-Authors: Susanne Dienst, Michael Abramovici, Madjid Fathi, Andreas Lindner
    Abstract:

    This paper describes a unifying data management concept for feedback assistance systems. The assistance system is to be integrated into existing system scenery. During the use of a hydraulic system, objective feedback such as sensor data or service data is captured and managed in local databases by the machine operators. The aim is to lead such Product Use Information (PUI) back into Product development. That way, the Product Developer uses the information to derive additional and innovative potential to improve next generation Products. The information flow is related in various systems i.e. the operator of the machine and the manufacturer. Furthermore, the PUI is managed inside the assistance system based on a data warehouse. The data warehouse is coupled with a Product Lifecycle Management (PLM) system, a well-known system to Product Developers. Within the PLM system, Product master data is created and managed. This also serves as the basis for the assistance system, so that the data models for both systems have to be amalgamated.

Susanne Dienst - One of the best experts on this subject based on the ideXlab platform.

  • Development of a knowledge-based feedback assistance system of Product use information for Product improvement
    International Journal of Product Development, 2014
    Co-Authors: Susanne Dienst, Michael Abramovici, Madjid Fathi, Andreas Lindner
    Abstract:

    Due to technological advancement, an increase in creating and storing digital data can be observed today, for instance throughout the Product life cycle. Through especially Product use, a large number of data are created. The data are mainly used during the Product use phase (e.g. condition-based maintenance). However, those data can be used as feedback to generate knowledge and support the Product Developer through improving future Product generations. This paper presents development and prototypical realisation of a feedback assistance system for the management, analysis and visualisation of feedback data. The system supports a Product Developer by improving the process of decision-making to discover development potentials. Thereupon, four modules have been developed to analyse related indicators statistically and to diagnose machine failures. The obtained knowledge about the current condition of machines should then be deployed to improve the next machine generations utilising the modules for decision support and prediction.

  • Use Case of Providing Decision Support for Product Developers in Product Improvement Processes
    Integration of Practice-Oriented Knowledge Technology: Trends and Prospectives, 2013
    Co-Authors: Michael Abramovici, Andreas Lindner, Susanne Dienst
    Abstract:

    Industrial goods like pumps, engines, and gears are subject of cyclical improvements. An important input for such Product updates is information from the use phase, especially information about failures that occurred during the use of current Products. In a current research project the authors have developed a concept and a prototype for a Feedback Assistant System. The first realized modules of this assistant provide filtered and condensed Product use information to the Product Developer. The paper in hands presents an extended concept and use case to assist the Product Developer in choosing the most suitable alternative in Product improvement processes. The decisions are based on hard facts using diverse criteria.

  • concept for improving industrial goods via contextual knowledge provision
    International Conference on Knowledge Management and Knowledge Technologies, 2012
    Co-Authors: Susanne Dienst, André Klahold, Michael Abramovici, Madjid Fathi, Andreas Lindner
    Abstract:

    At present, Product lifecycle data is provided, used, and archived only for very specific purposes. Textual data generated in Product use can be very comprehensive and contain valuable information beyond its original purpose, e.g. for Product development or improvement. This kind of information, however, is not fed back systematically, as its evaluation is currently not possible due to a lack of suitable methods and tools in Product development. The paper in hand presents a concept designed to support Product Developers by introducing maintenance, service, and customer data, which has undergone restructuring into textual form in the Product use phase, into Product development. To process the restructured textual data, customized text mining methods are generated as a part of knowledge management in Product development. These methods aim at identifying Products, Product generations, and failure descriptions, as well as the relationships among them. The knowledge gained through text mining is visualized in the work environment familiar to the Product Developer, and implements utilitarian visualization methods. Visualization is integrated into existing IT systems and provides knowledge required for Product improvement or development in a target-oriented way. This extension to knowledge-based Product development facilitates more efficient improvement of current and future Products.

  • A conceptual data management model of a feedback assistance system to support Product improvement
    2011 IEEE International Conference on Systems Man and Cybernetics, 2011
    Co-Authors: Susanne Dienst, Michael Abramovici, Madjid Fathi, Andreas Lindner
    Abstract:

    This paper describes a unifying data management concept for feedback assistance systems. The assistance system is to be integrated into existing system scenery. During the use of a hydraulic system, objective feedback such as sensor data or service data is captured and managed in local databases by the machine operators. The aim is to lead such Product Use Information (PUI) back into Product development. That way, the Product Developer uses the information to derive additional and innovative potential to improve next generation Products. The information flow is related in various systems i.e. the operator of the machine and the manufacturer. Furthermore, the PUI is managed inside the assistance system based on a data warehouse. The data warehouse is coupled with a Product Lifecycle Management (PLM) system, a well-known system to Product Developers. Within the PLM system, Product master data is created and managed. This also serves as the basis for the assistance system, so that the data models for both systems have to be amalgamated.

  • SMC - A conceptual data management model of a feedback assistance system to support Product improvement
    2011 IEEE International Conference on Systems Man and Cybernetics, 2011
    Co-Authors: Susanne Dienst, Michael Abramovici, Madjid Fathi, Andreas Lindner
    Abstract:

    This paper describes a unifying data management concept for feedback assistance systems. The assistance system is to be integrated into existing system scenery. During the use of a hydraulic system, objective feedback such as sensor data or service data is captured and managed in local databases by the machine operators. The aim is to lead such Product Use Information (PUI) back into Product development. That way, the Product Developer uses the information to derive additional and innovative potential to improve next generation Products. The information flow is related in various systems i.e. the operator of the machine and the manufacturer. Furthermore, the PUI is managed inside the assistance system based on a data warehouse. The data warehouse is coupled with a Product Lifecycle Management (PLM) system, a well-known system to Product Developers. Within the PLM system, Product master data is created and managed. This also serves as the basis for the assistance system, so that the data models for both systems have to be amalgamated.

Michael Abramovici - One of the best experts on this subject based on the ideXlab platform.

  • Development of a knowledge-based feedback assistance system of Product use information for Product improvement
    International Journal of Product Development, 2014
    Co-Authors: Susanne Dienst, Michael Abramovici, Madjid Fathi, Andreas Lindner
    Abstract:

    Due to technological advancement, an increase in creating and storing digital data can be observed today, for instance throughout the Product life cycle. Through especially Product use, a large number of data are created. The data are mainly used during the Product use phase (e.g. condition-based maintenance). However, those data can be used as feedback to generate knowledge and support the Product Developer through improving future Product generations. This paper presents development and prototypical realisation of a feedback assistance system for the management, analysis and visualisation of feedback data. The system supports a Product Developer by improving the process of decision-making to discover development potentials. Thereupon, four modules have been developed to analyse related indicators statistically and to diagnose machine failures. The obtained knowledge about the current condition of machines should then be deployed to improve the next machine generations utilising the modules for decision support and prediction.

  • Use Case of Providing Decision Support for Product Developers in Product Improvement Processes
    Integration of Practice-Oriented Knowledge Technology: Trends and Prospectives, 2013
    Co-Authors: Michael Abramovici, Andreas Lindner, Susanne Dienst
    Abstract:

    Industrial goods like pumps, engines, and gears are subject of cyclical improvements. An important input for such Product updates is information from the use phase, especially information about failures that occurred during the use of current Products. In a current research project the authors have developed a concept and a prototype for a Feedback Assistant System. The first realized modules of this assistant provide filtered and condensed Product use information to the Product Developer. The paper in hands presents an extended concept and use case to assist the Product Developer in choosing the most suitable alternative in Product improvement processes. The decisions are based on hard facts using diverse criteria.

  • Exploiting Service Data of Similar Product Items for the Development of Improved Product Generations by Using Smart Input Devices
    Lecture Notes in Production Engineering, 2013
    Co-Authors: Michael Abramovici, Andreas Krebs, Andreas Lindner
    Abstract:

    State-of-the-art industrial Products generate large amounts of data that is not lead back into Product development. The use of modern technologies like mobile devices and Auto-ID to identify Product items and collect data offers a new, rich data source that can be used by Product development. To gain an understanding of the Products in practical application, the collected data can be processed by assistant systems for the improvement of Products. The assistant system outlined in the paper in hand uses statistical methods and methods derived from risk management to provide a comprehensive analysis. A short overview of the analysis results is presented to the Product Developer as a preselection of parts worth improving. Based on the preselection, the Product Developer can choose specific parts and gain further information via the assistant system. The system itself provides that information using different methods of Product and information visualization.

  • concept for improving industrial goods via contextual knowledge provision
    International Conference on Knowledge Management and Knowledge Technologies, 2012
    Co-Authors: Susanne Dienst, André Klahold, Michael Abramovici, Madjid Fathi, Andreas Lindner
    Abstract:

    At present, Product lifecycle data is provided, used, and archived only for very specific purposes. Textual data generated in Product use can be very comprehensive and contain valuable information beyond its original purpose, e.g. for Product development or improvement. This kind of information, however, is not fed back systematically, as its evaluation is currently not possible due to a lack of suitable methods and tools in Product development. The paper in hand presents a concept designed to support Product Developers by introducing maintenance, service, and customer data, which has undergone restructuring into textual form in the Product use phase, into Product development. To process the restructured textual data, customized text mining methods are generated as a part of knowledge management in Product development. These methods aim at identifying Products, Product generations, and failure descriptions, as well as the relationships among them. The knowledge gained through text mining is visualized in the work environment familiar to the Product Developer, and implements utilitarian visualization methods. Visualization is integrated into existing IT systems and provides knowledge required for Product improvement or development in a target-oriented way. This extension to knowledge-based Product development facilitates more efficient improvement of current and future Products.

  • A conceptual data management model of a feedback assistance system to support Product improvement
    2011 IEEE International Conference on Systems Man and Cybernetics, 2011
    Co-Authors: Susanne Dienst, Michael Abramovici, Madjid Fathi, Andreas Lindner
    Abstract:

    This paper describes a unifying data management concept for feedback assistance systems. The assistance system is to be integrated into existing system scenery. During the use of a hydraulic system, objective feedback such as sensor data or service data is captured and managed in local databases by the machine operators. The aim is to lead such Product Use Information (PUI) back into Product development. That way, the Product Developer uses the information to derive additional and innovative potential to improve next generation Products. The information flow is related in various systems i.e. the operator of the machine and the manufacturer. Furthermore, the PUI is managed inside the assistance system based on a data warehouse. The data warehouse is coupled with a Product Lifecycle Management (PLM) system, a well-known system to Product Developers. Within the PLM system, Product master data is created and managed. This also serves as the basis for the assistance system, so that the data models for both systems have to be amalgamated.

Petter Gottschalk - One of the best experts on this subject based on the ideXlab platform.

  • Information Systems Leadership Roles
    Information Technology Management in Developing Countries, 2002
    Co-Authors: Petter Gottschalk
    Abstract:

    Information systems (IS) leadership roles have undergone fundamental changes over the past decade. Despite increased interest in recent years, little empirical research on IS managers has been done. This article presents results from a survey in Norway. The survey collected data on general leadership roles such as informational role, decisional role and interpersonal role, as well as on specific IS leadership roles such as chief architect, change leader, Product Developer, technology provocateur, coach and chief operating strategist. The empirical analysis indicates that strategic responsibility as well as network stage of growth influence the extent of informational role, while the extent to which the chief executive uses IT influences the extent of decisional role, and the extent to which subordinates use IT influence the extent of interpersonal role. IS managers with greater operating responsibility will be chief architects. The role of a change leader is positively influenced by the number of years in IT, the extent of IT use, the extent of strategic responsibility and the organisation’s revenue, while it is negatively influenced by the number of years in the current position. Product Developer can be predicted by strategic responsibility and chief executive’s IT use, while technology provocateur can be predicted by the extent of IT use. Coach can be predicted by the extent of subordinates’ IT use, and chief operating strategist can be predicted by the extent of strategic responsibility. Although several significant predictors of IS leadership roles were identified in this research, the search for more significant explanations should continue in future research.

  • Information Systems Leadership Roles: An Empirical Study of Information Technology Managers in Norway
    Journal of Global Information Management, 2000
    Co-Authors: Petter Gottschalk
    Abstract:

    Information systems (IS) leadership roles have undergone fundamental changes over the past decade. Despite increased interest in recent years, little empirical research on IS managers has been done. This article presents results from a survey in Norway. The survey collected data on general leadership roles such as informational role, decisional role and interpersonal role, as well as on specific IS leadership roles such as chief architect, change leader, Product Developer, technology provocateur, coach and chief operating strategist. The empirical analysis indicates that strategic responsibility as well as network stage of growth influence the extent of informational role, while the extent to which the chief executive uses IT influences the extent of decisional role, and the extent to which subordinates use IT influence the extent of interpersonal role. IS managers with greater operating responsibility will be chief architects. The role of a change leader is positively influenced by the number of years in IT, the extent of IT use, the extent of strategic responsibility and the organisation’s revenue, while it is negatively influenced by the number of years in the current position. Product Developer can be predicted by strategic responsibility and chief executive’s IT use, while technology provocateur can be predicted by the extent of IT use. Coach can be predicted by the extent of subordinates’ IT use, and chief operating strategist can be predicted by the extent of strategic responsibility. Although several significant predictors of IS leadership roles were identified in this research, the search for more significant explanations should continue in future research.

  • HICSS - IS/IT leadership roles
    Proceedings of the 33rd Annual Hawaii International Conference on System Sciences, 2000
    Co-Authors: Petter Gottschalk
    Abstract:

    Information systems (IS) and information technology (IT) leadership roles have undergone fundamental changes over the past decade. This paper presents a literature review and results from a survey in Norway. The survey collected data on general leadership roles such as informational role, decisional role and interpersonal role, as well as on IS/IT leadership roles such as chief architect, change leader, Product Developer, technology provocateur, coach and chief operating strategist. Empirical analysis indicates that strategic responsibility as well as network stage of growth influence the extent of informational role, while the extent to which the chief executive uses IT influences the extent of decisional role, and the extent to which subordinates use IT influence the extent of interpersonal role. IS/IT managers with greater operating responsibility will be chief architects. The role of a change leader is positively influenced by the number of years in IT, the extent of lT use, the extent of strategic responsibility and the organization's revenue, while it is negatively influenced by the number of years in the current position. Product Developer can be predicted by strategic responsibility and chief executive's IT use, while technology provocateur can be predicted by the extent of IT use coach can be predicted by the extent of subordinates' IT use, and chief operating strategist can be predicted by the extent of strategic responsibility.

Bennett J. Tepper - One of the best experts on this subject based on the ideXlab platform.

  • fat replacers and the functionality of fat in foods
    Trends in Food Science and Technology, 1994
    Co-Authors: Paula A Lucca, Bennett J. Tepper
    Abstract:

    Abstract Developing no- and low-fat Products is a high priority for the food industry. Given the variety of fat replacers available, how does a Product Developer decide which to use? Fat replacers can be divided into three classes on the basis of their composition: protein-based, carbohydrate-based and fat-based. Each has different functional properties that provide both advantages and limitations in specific applications. Presently there is no ‘silver bullet’ — no single fat replacer that contributes all of the desired sensory and functional qualities to all Products. A systems approach, one that makes use of a combination of two or more wisely chosen fat replacers, coupled with formula and procedural changes appears to be the best current strategy.