Knowledge-Intensive Processes: Characteristics, Requirements and Analysis of Contemporary Approaches

Engineering of knowledge-intensive processes (KiPs) is far from being mastered, since they are genuinely knowledge- and data-centric, and require substantial flexibility, at both design- and run-time. In this work, starting from a scientific literature analysis in the area of KiPs and from three real-world domains and application scenarios, we provide a precise characterization of KiPs. Furthermore, we devise some general requirements related to KiPs management and execution. Such requirements contribute to the definition of an evaluation framework to assess current system support for KiPs. To this end, we present a critical analysis on a number of existing process-oriented approaches by discussing their efficacy against the requirements

Identification and Categorization of Order Qualifiers and Order Winners in Knowledge Intensive Business Services

The increased number of companies supplying knowledge intensive business services (KIBS) has caused a highly competitive market during the recent decade, where actors on the market struggle to gain competitive advantage and especially vulnerable are companies that offer engineering services. Underlying factors for the difficulties to provide competitive services on the market for engineering services reside in the low entry barriers, a lot of players on the market, upcoming consultant brokers, a constantly accelerating technological development and similar value propositions among consultancy companies in this field. Due to these circumstances there is a need to find out what customers truly value when they purchasing engineering services. Firstly, which requirements must a company fulfill to qualify in the order process on the market for KIBS? And more importantly, which specific factors influence the customer’s final choice of supplier in this market? In order to answer these questions, this master thesis aims to identify and categorize order qualifier and order winner criteria in the KIBS industry. Furthermore, an objective is to understand the underlying factors, which impact the customer’s categorization of the identified criteria. The results from the competitive factors identified in the KIBS research and the already existing theories regarding order qualifying and order-winning criteria are combined into a theoretical framework. In order to gain deeper practical knowledge of the features customers consider as valuable in an engineering service, interviews with purchasers and development managers are conducted. The findings from the interviews are integrated with the preexisting theoretical template, resulting in a modified framework that takes empirical findings in account. Moreover, the interviews made it clear that it is not possible to divide the criteria into either order qualifying or order winning criteria. Therefore, a new category was added to the framework, which includes factors that are considered to be value adding, but neither order qualifying nor order winning. Finally, a framework of the identified and categorized order qualifiers, order winners and value adding factors in the knowledge intensive business service was developed. Due to the lack of appropriate theory that connects order qualifier and order-winner theory with knowledge intensive business services, this thesis bridge the gap between the two theoretical areas. Therefore, the main contribution to the academia is the identified and categorized order qualifier and order-winner criteria on the KIBS market. The identification of these criteria stresses what the customers value when purchasing engineering services, and the categorization of these criteria express the different importance of the factors. The latter enables consultancy companies to make an efficient prioritization of which criteria they should focus on while overlooking their value propositions

STAR framework revisited: Curriculum for user-centered design summer schools

Annually, an interdisciplinary community of students, researchers and practitioners from computer engineering, social sciences, Human Computer Interaction, visual communication and other related disciplines, gather together for 2-to-5 weeks to participate in intensive summer school sessions. Although the overall theme and the participants vary each year, these programs remain focused on the teaching and practice of User-Centered Design (UCD) in the context of the local community where the academy is conducted. By listening to lectures, working in ateliers, living with target users and facing real-world design problems, participants experientially learn a mixture of IxD processes, ethnographic methods, prototyping techniques and teamwork skills, despite the program's short duration. Intensive design summer academies like this are essential, as they offer an environment for experimentation that is difficult to create in other educational settings. However, organizing and implementing these programs in ways that optimize the learning process is challenging. As past participants, atelier leaders and instructors for a variety of summer workshops, the authors made several poignant observations about the need for an educational framework to facilitate learning and to address the students' diverse cultural backgrounds, educational disciplines, learning techniques and cultural markers. Upon further examination of the educational literature, ethnographic observation during subsequent summer sessions and interviews of past students, atelier leaders, lecturers and organizers, the authors proposed the STAR Framework for design summer schools. [see Schadewitz, Adler, Moncur, Roberts, 2006] While this framework offers organizers clear direction on structuring IxD summer schools, it provides little guidance on the curriculum itself. It has become clear that special attention must also be paid to the content, order and delivery of the curriculum, particularly given the limited time frame of the session. Building upon the established framework, this paper proposes a curricular construct that will maximize knowledge transfer within the summer school context

Enhancing Knowledge Intensive Business Processes via Knowledge Management Audit

Enhancing organizational Knowledge-Intensive Business Processes (KIBP) for gaining competitive advantages is often performed through Knowledge Management (KM) initiatives. These KM initiatives aim at developing organizational KM infrastructure of KIBP, starting from knowledge audit that is a necessary first step in any KM initiative. Current knowledge audit methods address either technological-related or social-related aspects. None of them was found to deal with the triple perspective of KM infrastructure: culture, knowledge processes and information technology, in the context of KIBP. This paper proposes a comprehensive framework and practical tools for knowledge audit that aim at enhancing KIBP by embedding KM capabilities within them. As KM infrastructure integrates social and technological disciplines, we developed a combined Socio-Engineering Knowledge Audit Methodology (SEKAM) for a systematic audit of the KM infrastructure in the context of KIBP. This methodology is illustrated through knowledge audit in a large high-tech global organization

Engineering Background Knowledge for Social Robots

Social robots are embodied agents that continuously perform knowledge-intensive tasks involving several kinds of information coming from different heterogeneous sources. Providing a framework for engineering robots' knowledge raises several problems like identifying sources of information and modeling solutions suitable for robots' activities, integrating knowledge coming from different sources, evolving this knowledge with information learned during robots' activities, grounding perceptions on robots' knowledge, assessing robots' knowledge with respect humans' one and so on. In this thesis we investigated feasibility and benefits of engineering background knowledge of Social Robots with a framework based on Semantic Web technologies and Linked Data. This research has been supported and guided by a case study that provided a proof of concept through a prototype tested in a real socially assistive context

From Case Histories to Conceptual Models

Geotechnical engineering deals with complicated and highly variable set of engineering principles. A typical geotechnical engineering project comprises site characterization, foundation / soil treatment design, execution, monitoring and quality control systems. Unlike some other civil engineering designs, highly variable soil conditions make a geotechnical designs an iterative and repetitive process which in-turn make these designs cost and time intensive. Economy and optimization of geotechnical designs are dependent on comprehensive site characterization and evaluation of multiple alternatives. Availability of up-to-date data sets of geotechnical case histories covering entire spectrum; from techniques / technologies to results can help reduce both cost and time of future geotechnical projects. Knowledge from case histories can be used to develop geotechnical constitutive and analytical models with the help of information technology; such models can lead us to many progressive and futuristic limits of geotechnical engineering. The authors of the paper intend to propose architectural development of “Geotechnical Information System (GTIS)”. The GTIS system covering fundamental geotechnical concepts, data of case histories such as; techniques, technologies employed, monitoring and quality control systems, results / effectiveness of techniques, will provide a framework for the following: • increased understanding of world-wide geotechnical issues by sharing lessons learnt which will help minimize barriers of uncertainty • enhancement of investigation and design procedures • development of economical and efficient technologies • identification of areas for collaborative research • development of “Geotechnical Artificial Intelligence Systems (GTAIS)

Knowledge-based engineering and computer vision for configuration-based substation design

Introduction: As the increase in electrification poses new demands on power delivery, the quality of the distribution system is paramount. Substations are a critical part of power grids that allow for control and service of the electrical distribution system. Substations are currently developed in a project-based and manually intensive manner, with a high degree of manual work and lengthy lead times. Substations are primarily sold through tenders that are accompanied by an inherent need for engineering-to-order activities. Although necessary, these activities present a paradox as tender processes must be agile and fast. To remedy this shortcoming, this article outlines a knowledge capture and reuse methodology to standardize and automate the product development processes of substation design.Methods: A novel framework for substation design is presented that implements knowledge-based engineering (KBE) and artificial intelligence methods in computer vision to capture knowledge. In addition, a product configuration system is presented, utilizing high-level CAD templates. The development has followed the KBE methodology MOKA.Results: The proposed framework has been implemented on several company cases where three (simplified) are presented in this paper. The framework decreased the time to create a 3D model from a basic electric single line diagram by performing the identification and design tasks in an automated fashion.Discussion: Ultimately, the framework will allow substation design companies to increase competitiveness through automation and knowledge management and enable more tenders to be answered without losing engineering quality

Context-aware Process Management for the Software Engineering Domain

Historically, software development projects are challenged with problems concerning budgets, deadlines and the quality of the produced software. Such problems have various causes like the high number of unplanned activities and the operational dynamics present in this domain. Most activities are knowledge-intensive and require collaboration of various actors. Additionally, the produced software is intangible and therefore difficult to measure. Thus, software producers are often insufficiently aware of the state of their source code, while suitable software quality measures are often applied too late in the project lifecycle, if at all. Software development processes are used by the majority of software companies to ensure the quality and reproducibility of their development endeavors. Typically, these processes are abstractly defined utilizing process models. However, they still need to be interpreted by individuals and be manually executed, resulting in governance and compliance issues. The environment is sufficiently dynamic that unforeseen situations can occur due to various events, leading to potential aberrations and process governance issues. Furthermore, as process models are implemented manually without automation support, they impose additional work for the executing humans. Their advantages often remain hidden as aligning the planned process with reality is cumbersome. In response to these problems, this thesis contributes the Context-aware Process Management (CPM) framework. The latter enables holistic and automated support for software engineering projects and their processes. In particular, it provides concepts for extending process management technology to support software engineering process models in their entirety. Furthermore, CPM contributes an approach to integrate the enactment of the process models better with the real-world process by introducing a set of contextual extensions. Various events occurring in the course of the projects can be utilized to improve process support and activities outside the realm of the process models can be covered. That way, the continuously growing divide between the plan and reality that often occurs in software engineering projects can be avoided. Finally, the CPM framework comprises facilities to better connect the software engineering process with other important aspects and areas of software engineering projects. This includes automated process-oriented support for software quality management or software engineering knowledge management. The CPM framework has been validated by a prototypical implementation, various sophisticated scenarios, and its practical application at two software companies