textA term map is a map that visualizes the structure of a scientific field by showing the relations between important terms in the field. The terms shown in a term map are usually selected manually with the help of domain experts. Manual term selection has the disadvantages of being subjective and labor-intensive. To overcome these disadvantages, we propose a methodology for automatic term identification and we use this methodology to select the terms to be included in a term map. To evaluate the proposed methodology, we use it to construct a term map of the field of operations research. The quality of the map is assessed by a number of operations research experts. It turns out that in general the proposed methodology performs quite well.

/pdf/automatic-term-identification-for-bibliometric-mapping-1utn18clpt.pdf

Automatic Term Identification for Bibliometric Mapping

In the Systems Engineering (SE) domain there has been a paradigm shift from document-based to model-based system development artefacts; in fact, new methodologies are emerging to meet the increasing complexity of current systems and the corresponding growing need of digital workflows. In this regard, Model-Based Systems Engineering (MBSE) is considered as a key enabler by many central players of the SE community. MBSE has reached an adequate level of maturity and there exist documented success stories in its adoption in industry. In particular, one significant benefit of utilising MBSE when compared to the traditional manual and document-centric workflows is that models are available from early phases of systems development; these enable a multitude of analyses prior any implementation effort together with other relevant capabilities, like the automation of development tasks. Nonetheless, it is noticeable there is a lack of a common understanding for how formal analyses for the verification and validation (V&V) of systems behaviour, specifically in the early phases of development, could be placed in an MBSE setting.
 
 In this article, we report on the planning, execution, and results of a systematic literature review regarding the early V&V of systems behaviour in the context of model-based systems engineering. The review aims to provide a structured representation of the state-of-the-art with respect to motivations, proposed solutions, and limitations. From an initial set of potentially relevant 701 peer-reviewed publications we selected 149 primary studies, which we analysed according to a rigorous data extraction, analysis, and synthesis process. Based on our results, early V&V has usually the goal of checking the quality of a system design to avoid discovering flaws when parts are being concretely realised; SysML is a
 de facto
 standard for describing the system under study, while the solutions for the analyses tend to be varied; also V&V analyses tend to target varied properties with a slight predominance of functional concerns, and following the variation mentioned so far the proposed solutions are largely context specific; the proposed approaches are usually presented without explicit limitations, while when limitations are discussed, readiness of the solutions, handling of analyses simplifications/assumptions, and languages/tools integration are among the most frequently mentioned issues.
 
 Based on the survey results and the standard SE practices, we discuss how the current state-of-the-art MBSE supports early V&V of systems behaviour with a special focus on industrial adoption, and identify relevant challenges to be researched further.

Early Validation and Verification of System Behaviour in Model-Based Systems Engineering: A Systematic Literature Review

After mass production and then mass customization, the time is almost ripe for mass personalization. The goal is to offer unique products designed for the needs of each customer. However, production in larger series of products also has its advantages, and the promise of “lot size one” is still far from being the norm in several sectors of the economy. As a result of an action research project in a small household ceramic producer, this paper explores the potential of a hybrid strategy. Augmented digital engineering is adopted to (1) ensure customer participation along the entire product design lifecycle, (2) maintain the benefits of modularization and low cost, (3) minimize the waste of time and materials during product design, and (4) seek a minimum trade-off between customer desires and engineering strategy. For theory, our work describes Industry 4.0 technology's role in achieving individual customer interaction and value co-creation in hybrid strategies of mass customization and mass personalization. For practice, we present an example of technological architecture to implement augmented digital engineering in Industry 4.0, accessible to scenarios of hand-intensive work and creative design processes. 

https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/sys.21682

Mass customization and mass personalization meet at the crossroads of Industry 4.0: A case of augmented digital engineering

Advanced manufacturing technologies play an important role in keeping production in high‐cost countries. Due to their flexibility, robot‐based solutions have been one of the major enablers in establishing advanced manufacturing capabilities in the traditional high‐cost countries. This paper concerns the problem of automated deburring of cast parts. If performed manually, this operation introduces major health, safety, and environmental (HSE) concerns. As such, removal of highly variable casting burrs in the Norwegian context requires a solution based on robots, smart sensors, and advanced algorithms to tackle the problem in a flexible and cost‐effective way. Due to the complexity of the task, one is confronted with a breadth of various alternatives to choose from when realizing the desired functionality. These alternatives expand as one considers a pipeline of the subtasks involved in the process. The decisions made in each step cascade throughout the whole pipeline. To tackle the complexity while developing a robotized deburring system, a systemic approach based on cascading trade‐off studies is proposed in this paper. This paper is also a contribution to the gap in the literature for cases of trade‐off studies in the domain of mechanical engineering. The SPADE (stakeholders, problem formulation, analysis, decision making, and evaluation) methodology has been used as a framework to resolve automation of complex mechanical engineering manufacturing process decisions. The systems engineering (SE) approach proved useful to identify and prioritize the stakeholders and their needs, as well as analyzing the different alternatives in a complex engineering system when dealing with cascading trade studies.

Cascading trade‐off studies for robotic deburring systems

Economic decisions are a crucial part of the engineering design process as designers aim to minimize the cost and maximize the system’s benefits. This study focuses on first-year undergraduate students’ economic decision-making process when they trade off costs and benefits during a design challenge. In addition, we characterized students’ patterns of outcomes derived from economic decisions using the cost-benefit analysis (CBA) method during the design process. Our results suggest that students took different approaches, such as being conservative, moderately conservative, moderate, and aggressive when they tradeoff their design goals. Implications of this study relate to (a) the characterization of different approaches for trading-off design goals and (b) the use of the cost-benefit analysis method as a tool to assess students’ final designs to decide which alternative design is better. In addition, students can use the CBA method to make informed decisions while designing to optimize their design solutions. 

First-year undergraduate students’ economic decision outcomes in engineering design

System design and engineering trade-off analytics: State of the published practice

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System design and engineering trade-off analytics: State of the published practice