828,823 research outputs found

    A framework for business process model repositories

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    Large organizations often run hundreds or even thousands of business processes. Managing such large collections of business processes is a challenging task. Intelligent software can assist in that task by providing common repository functions such as storage, search and version management. They can also provide advanced functions that are specific for managing collections of process models, such as managing the consistency of public and private processes and extracting knowledge from existing processes to better design new processes. This paper, by analyzing existing business process model repositories, proposes a framework for repositories that assist in managing large collections of business process models. The framework consists of a management model and a reference architecture. The management model lists the functionality that can be provided by business process model repositories. The reference architecture presents the components that provide this functionality and their interconnections. The framework provides a reference model for analysis and extension of existing repositories and design of new repositories

    Optimal management of bio-based energy supply chains under parametric uncertainty through a data-driven decision-support framework

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    This paper addresses the optimal management of a multi-objective bio-based energy supply chain network subjected to multiple sources of uncertainty. The complexity to obtain an optimal solution using traditional uncertainty management methods dramatically increases with the number of uncertain factors considered. Such a complexity produces that, if tractable, the problem is solved after a large computational effort. Therefore, in this work a data-driven decision-making framework is proposed to address this issue. Such a framework exploits machine learning techniques to efficiently approximate the optimal management decisions considering a set of uncertain parameters that continuously influence the process behavior as an input. A design of computer experiments technique is used in order to combine these parameters and produce a matrix of representative information. These data are used to optimize the deterministic multi-objective bio-based energy network problem through conventional optimization methods, leading to a detailed (but elementary) map of the optimal management decisions based on the uncertain parameters. Afterwards, the detailed data-driven relations are described/identified using an Ordinary Kriging meta-model. The result exhibits a very high accuracy of the parametric meta-models for predicting the optimal decision variables in comparison with the traditional stochastic approach. Besides, and more importantly, a dramatic reduction of the computational effort required to obtain these optimal values in response to the change of the uncertain parameters is achieved. Thus the use of the proposed data-driven decision tool promotes a time-effective optimal decision making, which represents a step forward to use data-driven strategy in large-scale/complex industrial problems.Peer ReviewedPostprint (published version

    Blockchain and Organizational Characteristics : Towards Business Model Innovation

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    Blockchain seems to challenge the current business models by providing opportunities for new value creation. However, several research gaps remain in literature in evaluating how firms can leverage new approaches to innovation management and opportunities created by blockchain. Supporting organizational characteristics affecting digital innovation management process also need attention in order to challenge the traditional theories while developing unique fundamental assumptions between innovation processes and outcomes. Thus, blockchain and organizational characteristics need to be understood as an encompassing, overarching and interrelated ecosystem in digital innovation management. Grounding on digitalization and innovation management, this research conceptualizes how blockchain technology and supporting organizational characteristics (i.e., R&D investment, strategic alignment, cultural support, top management knowledge and involvement, insights from customers and end-users) can be integrated for business model innovation. This research develops a conceptual framework involving multi-disciplinary collaborative actions that strengthen and empower business model innovation.©2020 Springer. This is a post-peer-review, pre-copyedit version of an article published in Advances in Creativity, Innovation, Entrepreneurship and Communication of Design: Proceedings of the AHFE 2020 Virtual Conferences on Creativity, Innovation and Entrepreneurship, and Human Factors in Communication of Design, July 16-20, 2020, USA. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-030-51626-0_9.fi=vertaisarvioitu|en=peerReviewed

    Distributed IT for integration and communication of engineering information for collaborative building design

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    In recent years, the rapid development of new information technologies has significantly impacted on the product development process as strategic means to gain competitive advantage in a global market. In the engineering domain, powerful computer-based tools such as Computer Aided Design systems enable engineers to perform various design tasks and realise product concepts in the early phase of the product development process. However, the increasing complexity of modern products as well as the globalization of product development further necessitate distributed and collaborative design environments. This is where different computer systems and dispersed specialists in similar or different disciplines need to collaboratively be involved in shared design activities. Therefore, the integration and communication of engineering information are two of the most key technical factors in ensuring successful collaboration. The current application of information technology in supporting collaboration during the design process is limited to either a document-based or a common format-based exchange level. These methods provide relatively simple forms of collaboration compared with desired distributed and collaborative design environments that can deliver more effective ways of collaboration. The work detailed in this research investigates the advantages of using modern distributed information technologies alongside a suitable framework and a product model to support multi-disciplinary collaborative design. The work also involves exploring other important issues related to real-time collaborative design environments. These are design transaction management, access control, communication, and version management. The research work employs modern technology and distributed computing to enhance the processes of collaborative building design. The research proposes a framework and a product model to extend the functionalities of stand-alone and single-user design systems to facilitate synchronous collaborative design where distributed designers can work concurrently on a centralised shared model and carry out all necessary communication and data exchanges electronically. The implemented framework proposes a data transaction management approach that ensures efficient concurrent access to the model data and maintains data consistency. The framework also employs software agents to automatically access and operate on the information exchanged among the collaborators. The proposed product model in this work extends an adopted model to support access right control and version management. The work is implemented in an experimental software as a client-server model. .Net technology is used for implementing the framework and the product model and virtual reality technology is used to allow for intuitive interaction with the system. The research concludes that the utilisation of the modern distributed technologies can effectively induce change in the design process toward a more collaborative and concurrent design. As demonstrated within this work, these technologies with a suitable system design can meet the main requirements of a real-time collaborative building design system

    Goal-driven agent-oriented software processes

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    The quality of software processes is acknowledged as a critical factor for delivering quality software systems. Any initiative for improving the quality of software processes requires their explicit representation and management. A current representational metaphor for systems is agent orientation, which has become one of the recently recognized engineering paradigms. In this article, we argue for the convenience of representing the software process using an agent-oriented language to model it and a goal-driven procedure to design it. Particularly we propose using the i* framework which is both an agent- and a goal-oriented modeling language. We review the possibilities of i* as a software process modeling language, and we also show how success factors can be made explicit in i* representations of the software processes. Finally, we illustrate the approach with an example based on the development of a set of ergonomic and safety software tools.Peer ReviewedPostprint (published version

    Distributed IT for integration and communication of engineering information for collaborative building design

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    In recent years, the rapid development of new information technologies has significantly impacted on the product development process as strategic means to gain competitive advantage in a global market. In the engineering domain, powerful computer-based tools such as Computer Aided Design systems enable engineers to perform various design tasks and realise product concepts in the early phase of the product development process. However, the increasing complexity of modern products as well as the globalization of product development further necessitate distributed and collaborative design environments. This is where different computer systems and dispersed specialists in similar or different disciplines need to collaboratively be involved in shared design activities. Therefore, the integration and communication of engineering information are two of the most key technical factors in ensuring successful collaboration. The current application of information technology in supporting collaboration during the design process is limited to either a document-based or a common format-based exchange level. These methods provide relatively simple forms of collaboration compared with desired distributed and collaborative design environments that can deliver more effective ways of collaboration. The work detailed in this research investigates the advantages of using modern distributed information technologies alongside a suitable framework and a product model to support multi-disciplinary collaborative design. The work also involves exploring other important issues related to real-time collaborative design environments. These are design transaction management, access control, communication, and version management. The research work employs modern technology and distributed computing to enhance the processes of collaborative building design. The research proposes a framework and a product model to extend the functionalities of stand-alone and single-user design systems to facilitate synchronous collaborative design where distributed designers can work concurrently on a centralised shared model and carry out all necessary communication and data exchanges electronically. The implemented framework proposes a data transaction management approach that ensures efficient concurrent access to the model data and maintains data consistency. The framework also employs software agents to automatically access and operate on the information exchanged among the collaborators. The proposed product model in this work extends an adopted model to support access right control and version management. The work is implemented in an experimental software as a client-server model. .Net technology is used for implementing the framework and the product model and virtual reality technology is used to allow for intuitive interaction with the system. The research concludes that the utilisation of the modern distributed technologies can effectively induce change in the design process toward a more collaborative and concurrent design. As demonstrated within this work, these technologies with a suitable system design can meet the main requirements of a real-time collaborative building design system

    Application of the Design Structure Matrix (DSM) to the real estate development process

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    Thesis (S.M.)--Massachusetts Institute of Technology, Program in Real Estate Development in Conjunction with the Center for Real Estate, 2009.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student submitted PDF version of thesis.Includes bibliographical references (p. 93-95).This thesis presents a pioneering application of an engineering systems framework, the Design Structure Matrix (DSM), to model the real estate development (RED) process. The DSM is a process modeling tool that originated recently in the branches of engineering systems and management science, and is primarily used to study product development processes. The DSM is an n-squared graphical matrix representation of a process that is particularly well suited to model both the sequential and iterative informational relationships between tasks in a product development process. The similarities between product development and the real estate development process make DSM an excellent fit for applying the DSM. The thesis first reviews existing models of the RED process but finds them lacking a combination of granularity and ability to model the highly iterative nature of the RED process. This limits their effectiveness for conveying information useful to practitioners. No previous RED model describes the process at a task level or has the ability to model iterative or sequential information flows between tasks. The DSM developed in this thesis first presents a normative or baseline model of a RED project. The model was developed through the participation and assistance of MIT/CRE industry partner, Jones Lang LaSalle (Boston Office). Through a series of interviews and meetings, the authors first developed a Six Stage Event Sequence model of RED with decision-gates found to occur during the process. The six stages were then expanded with JLL's assistance into a table of 91 individual tasks necessary for successful completion of a RED project.(cont.) Finally, again with JLL's engagement, the 91X91 'Baseline' RED process DSM was constructed, identifying 1,148 planned informational inter-task interactions (out of 8,281 potential interactions). The 'Baseline' DSM model was then manipulated to highlight important aspects of the RED process including the iterative and interdisciplinary nature of RED. Several typical development scenarios are then modeled to highlight the utility of DSM as a management tool in practice. The models show how unplanned iteration can become a significant cause of project risk and failure. They also highlight the risks and opportunities that task re-sequencing can have on a project. This thesis demonstrates the DSM to be a useful and effective model of the RED process enabling new insight and understanding. The highly complex and iterative RED process can be graphically modeled in great detail in a visually appealing manner. Additionally, the RED DSM proves to be an adaptive and manipulative tool that allows for a multi-layer grasping of the RED process, able to assist in project management, change management, identification of risks and opportunities, and firm-level organizational structure and procedures. Additionally, the RED DSM model proves to be a useful pedagogical device for teaching real estate students.by Benjamin Bulloch and John Sullivan.S.M

    The 2P-K Framework: A Personal Knowledge Measurement Framework for the Pharmaceutical Industry

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    Knowledge is a dynamic human process to justify our personal belief in pursuit of the truth. The intellectual output of any organisation is reliant upon the individual people within that organisation. Despite the eminent role of personal knowledge in organisations, personal knowledge management and measurement have received little attention, particularly in pharmaceutical manufacturing. The pharmaceutical industry is one of the pillars of the global economy and a knowledge-intensive sector where knowledge is described as the second product after medicines. The need of measurement to achieve effective management is not a new concept in management literature. This study offers an explanatory framework for personal knowledge, its underlying constructs and observed measures in the pharmaceutical manufacturing context. Following a sequential mixed method research (MMR) design, the researcher developed a measurement framework based on the thematic analysis of fifteen semi-structured interviews with industry experts and considering the extant academic and regulatory literature. A survey of 190 practitioners from the pharmaceutical manufacturing sector enabled quantitative testing and validation of the proposed models utilising confirmatory factor analysis. The pharmaceutical personal knowledge framework was the fruit of a comprehensive study to explain and measure the manifestations of personal knowledge in pharmaceutical organisations. The proposed framework identifies 41 personal knowledge measures reflecting six latent factors and the underlying personal knowledge. The hypothesised factors include: regulatory awareness, performance, wisdom, organisational understanding, mastership of product and process besides communication and networking skills. In order to enhance the applicability and flexibility of the measurement framework, an abbreviated 15-item form of the original framework was developed. The abbreviated pharmaceutical personal knowledge (2P-K) framework demonstrated superior model fit, better accuracy and reliability. The research results reveal that over 80% of the participant pharmaceutical organisations had a form of structured KM system. However, less than 30% integrated KM with corporate strategies suggesting that KM is still in the early stages of development in the pharmaceutical industry. Also, personal knowledge measurement is still a subjective practice and predominately an informal process. The 2P-K framework offers researchers and scholars a theoretically grounded original model for measuring personal knowledge. Also, it offers a basis for a personal knowledge measurement scale (2P-K-S) in the pharmaceutical manufacturing context. Finally, the study had some limitations. The framework survey relied on self-ratings. This might pose a risk of social desirability bias and Dunning–Kruger effect. Consequently, a 360- degree survey was suggested to achieve accurate assessments. Also, the model was developed and tested in an industry-specific context. A comparative study in similar manufacturing industries (e.g. chemical industries) is recommended to assess the validity of the current model or a modified version of it in other industries

    Boundary negotiations: a paradox theoretical approach for efficient and flexible modular systems

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    This is the author accepted manuscript. The final version is available from Emerald via the DOI in this recordPurpose: The purpose of this paper is to explore the interplay between firm boundary decisions and the management of both-and efficiency and flexibility and the implications this has for modular design in the provision of advanced services. Design/Methodology/Approach: A single case study in the defence industry employs semistructured interviews supplemented by secondary data. Data is analysed using thematic analysis. Findings: The findings provide a process model of boundary negotiations for the design of efficient and flexible modular systems consisting of three phases; boundary ambiguity, boundary defences and boundary alignment. Practical implications: The study provides a process framework for boundary negotiations to help organisations navigate the management of both-and efficiency and flexibility in the provision of advanced services. Originality/Value: Drawing upon modularity, paradox and systems theory, this article provides novel theoretical insight into the relationship between firm boundary decisions and the management of bothand efficiency vs. flexibility in the provision of product upgrade services.Engineering and Physical Sciences Research Council (EPSRC

    GitFL: Adaptive Asynchronous Federated Learning using Version Control

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    As a promising distributed machine learning paradigm that enables collaborative training without compromising data privacy, Federated Learning (FL) has been increasingly used in AIoT (Artificial Intelligence of Things) design. However, due to the lack of efficient management of straggling devices, existing FL methods greatly suffer from the problems of low inference accuracy and long training time. Things become even worse when taking various uncertain factors (e.g., network delays, performance variances caused by process variation) existing in AIoT scenarios into account. To address this issue, this paper proposes a novel asynchronous FL framework named GitFL, whose implementation is inspired by the famous version control system Git. Unlike traditional FL, the cloud server of GitFL maintains a master model (i.e., the global model) together with a set of branch models indicating the trained local models committed by selected devices, where the master model is updated based on both all the pushed branch models and their version information, and only the branch models after the pull operation are dispatched to devices. By using our proposed Reinforcement Learning (RL)-based device selection mechanism, a pulled branch model with an older version will be more likely to be dispatched to a faster and less frequently selected device for the next round of local training. In this way, GitFL enables both effective control of model staleness and adaptive load balance of versioned models among straggling devices, thus avoiding the performance deterioration. Comprehensive experimental results on well-known models and datasets show that, compared with state-of-the-art asynchronous FL methods, GitFL can achieve up to 2.64X training acceleration and 7.88% inference accuracy improvements in various uncertain scenarios
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