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This paper aims to introduce a novel method for the analysis of open cell porous components fabricated by laser-based powder bed metal additive manufacturing (AM) for the purpose of quality control. This method uses photogrammetric analysis, the extraction of geometric information from an image through the use of algorithms. By applying this technique to porous AM components, a rapid, low-cost inspection of geometric properties such as material thickness and pore size is achieved. Such measurements take on greater importance, as the production of porous additive manufactured orthopaedic devices increases in number, causing other, slower and more expensive methods of analysis to become impractical.

Here the development of the photogrammetric method is discussed and compared to standard techniques including scanning electron microscopy, micro computed tomography scanning and the recently developed focus variation (FV) imaging. The system is also validated against test graticules and simple wire geometries of known size, prior to the more complex orthopaedic structures.

The photogrammetric method shows an ability to analyse the variability in build fidelity of AM porous structures for use in inspection purposes to compare component properties. While measured values for material thickness and pore size differed from those of other techniques, the new photogrammetric technique demonstrated a low deviation when repeating measurements, and was able to analyse components at a much faster rate and lower cost than the competing systems, with less requirement for specific expertise or training.

The advantages demonstrated by the image-based technique described indicate the system to be suitable for implementation as a means of in-line process control for quality and inspection applications, particularly for high-volume production where existing methods would be impractical.

The open science movement calls for transparent and retraceable research processes. While infrastructures to support these practices in qualitative research are lacking, the design needs to consider different approaches and workflows. The paper bases on the definition of ontologies as shared conceptualizations of knowledge (Borst, 1999). The authors argue that participatory design is a good way to create these shared conceptualizations by giving domain experts and future users a voice in the design process via interviews, workshops and observations.

This paper presents a novel approach for creating ontologies in the field of open science using participatory design. As a case study the creation of an ontology for qualitative coding schemas is presented. Coding schemas are an important result of qualitative research, and reuse can yield great potential for open science making qualitative research more transparent, enhance sharing of coding schemas and teaching of qualitative methods. The participatory design process consisted of three parts: a requirement analysis using interviews and an observation, a design phase accompanied by interviews and an evaluation phase based on user tests as well as interviews.

The research showed several positive outcomes due to participatory design: higher commitment of users, mutual learning, high quality feedback and better quality of the ontology. However, there are two obstacles in this approach: First, contradictive answers by the interviewees, which needs to be balanced; second, this approach takes more time due to interview planning and analysis.

The implication of the paper is in the long run to decentralize the design of open science infrastructures and to involve parties affected on several levels.

In ontology design, several methods exist by using user-centered design or participatory design doing workshops. In this paper, the authors outline the potentials for participatory design using mainly interviews in creating an ontology for open science. The authors focus on close contact to researchers in order to build the ontology upon the expert's knowledge.

The purpose of this paper is to present a methodology for research through game design and discuss how simulation games can be used to bridge the gap between operational exercises and simulation or analytical modelling and to provide guidelines on how simulation games can be designed for different research purposes in the context of humanitarian logistics.

This paper combines a literature review on gaming as a research method with an analysis of requirements for humanitarian logistics research methods. Starting from this theoretical framework, the authors develop a design thinking approach that highlights how games can be used for different research purposes. To illustrate the approach, the authors develop two different game set-ups that are of increasing fidelity and complexity. Finally, the authors discuss the results of the evaluation of both approaches, reflect on the design choices and provide recommendations for research and practice.

Gaming is a suitable research method to explore and analyse behaviour and decisions in emergent settings that require team work and collaborative problem solving. Especially when safety and security concerns may hinder access and experimentation on site, gaming can offer a realistic and engaging quasi-experimental environment. The aspects of engagement and realism also make gaming a suitable tool to combine training and research.

Although the use of games has attracted some attention in commercial supply chain management and crisis response, there is no systematic overview of gaming as a research method in humanitarian logistics. This paper is set to make a headway in addressing this gap by proposing a concrete approach to design games for humanitarian logistics research.

The paper attempts to address the following research questions (RQs): RQ1: What are the main research topics within PSS research? RQ2: What are future trends for PSS research?

Twenty years of research (1999–2018) on product-service systems (PSS) produced a significant amount of scientific literature on the topic. As the PSS field is relatively new and fragmented across different disciplines, a review of the prior and relevant literature is important in order to provide the necessary framework for understanding current developments and future perspectives. This paper aims to review and organize research contributions regarding PSS. A machine-learning algorithm, namely Latent Dirichlet Allocation, has been applied to the whole literature corpus on PSS in order to understand its structure.

The adopted approach resulted in the definition of eight distinct and representative topics able to deal adequately with the multidisciplinarity of the PSS. Furthermore, a systematic review of the literature is proposed to summarize the state-of-the-art and limitations in the identified PSS research topics. Based on this critical analysis, major gaps and future research challenges are presented and discussed.

On the basis of the results of the topic landscape, the paper presents some potential research opportunities on PSSs. In particular, challenges, transversal to the eight research topics and related to recent technology trends and digital transformation, have been discussed.

The purpose of this paper is to show how data analytics can be used to identify areas of potential cost savings for category managers of installation-level services. Using integrated solid waste management (ISWM) as a test case, the authors also examine the impact of small business set-asides on price and contractor performance.

The authors use data analytics, specifically sequential regression, the Wilcoxon rank-sum test and ordered logistic regression to investigate the influence of service- and contracting-related variables on price and contractor performance.

The authors find that service- and contracting-related variables influence price. Specifically, they identify that a service-related variable, number of containers, significantly affects price, and that two contracting-related variables, one type of small business set-aside and the number of offers received, also significantly affect price. The authors quantify the price premiums paid for using various types of small business set-asides.

Although the findings were significant, the authors believe that the robustness of the conclusions could be enhanced if the Air Force captured more data. Additional observations would increase the generalizability of the results.

This empirical experiment demonstrates that detailed analyses are required to gain insights into services’ price drivers to craft more appropriate category management strategies for installation-level services.

This empirical study shows how historical data can be used to assess price drivers of installation-level services. It is also one of the first to quantify the impact that small business set-asides have on price.

This study aims to introduce the DoraHand, and the basic capability and performance have been verified in this paper. Besides the idea of sharing modular design and sensor design, the authors want to deliver an affordable and practical dexterous hand to the research area to contribute to the robotic manipulation area.

This paper introduced the DoraHand, a novel scalable and practical modular dexterous hand, which, adopting modular finger and palm design, fully actuated joint and tactile sensors, can improve the dexterity for robotic manipulation and lower the complexity of maintenance. A series of experiments are delivered to verify the performance of the hand and sensor module.

The parameters of the DoraHand are verified and suitable for the research of robotics manipulation area, the sensing capability has been tested with the static experiment and the slip prediction algorithm. And, the advantage of modular design and extensible interface have been verified by the real application.

The authors continue improving the DoraHand and extend it to more different applications. The authors want to make the DoraHand as a basic research platform in the robotic manipulation area.

The DoraHand has been sent to more than ten different research institutes for different research applications. The authors continue working on this hand for better performance, easier usage and more affordability.

This kind of dexterous hand can help researchers get rid of complex physical issues and pay more attention to the algorithm part; it can help to make robotic manipulation work more popular.

The key design in the DoraHand is the modular finger and sensing module. With the special design in mechanical and electrical parts, the authors build reliable hardware and can support the diversity requirement in the robotic manipulation area. The hand with tactile sensing capability can be used in more research and applications with its extensibility.

In many security domains, the ‘human in the system’ is often a critical line of defence in identifying, preventing and responding to any threats (Saikayasit, Stedmon, & Lawson, 2015). Traditionally, such security domains are often focussed on mainstream public safety within crowded spaces and border controls, through to identifying suspicious behaviours, hostile reconnaissance and implementing counter-terrorism initiatives. More recently, with growing insecurity around the world, organisations have looked to improve their security risk management frameworks, developing concepts which originated in the health and safety field to deal with more pressing risks such as terrorist acts, abduction and piracy (Paul, 2018). In these instances, security is usually the specific responsibility of frontline personnel with defined roles and responsibilities operating in accordance with organisational protocols (Saikayasit, Stedmon, Lawson, & Fussey, 2012; Stedmon, Saikayasit, Lawson, & Fussey, 2013). However, understanding the knowledge that frontline security workers might possess and use requires sensitive investigation in equally sensitive security domains.

This chapter considers how to investigate knowledge elicitation in these sensitive security domains and underlying ethics in research design that supports and protects the nature of investigation and end-users alike. This chapter also discusses the criteria used for ensuring trustworthiness as well as assessing the relative merits of the range of methods adopted.

Buildings and their use is a complex process from design to occupation. Buildings produce huge volumes of data such as building information modelling (BIM), sensor (e.g. from building management systems), occupant and building maintenance data. These data can be spread across multiple disconnected systems in numerous formats, making their combined analysis difficult. The purpose of this paper is to bring these sources of data together, to provide a more complete account of a building and, consequently, a more comprehensive basis for understanding and managing its performance.

Building data from a sample of newly constructed housing units were analysed, several properties were identified for the study and sensors deployed. A sensor agnostic platform for visualising real-time building performance data was developed.

Data sources from both sensor data and qualitative questionnaire were analysed and a matrix of elements affecting building performance in areas such as energy use, comfort use, integration with technology was presented. In addition, a prototype sensor visualisation platform was designed to connect in-use performance data to BIM.

This work presents initial findings from a post occupancy evaluation utilising sensor data. The work attempts to address the issues of BIM in-use scenarios for housing sector. A prototype was developed which can be fully developed and replicated to wider housing projects. The findings can better address how indoor thermal comfort parameters can be used to improve housing stock and even address elements such as machine learning for better buildings.

A maturity model for Industry 4.0 (I4.0 MM) with influencing factors is designed to address maturity issues in adopting Industry 4.0. Standardisation in I4.0 supports manufacturing industry transformation, forming reference architecture models (RAMs). This paper aligns key factors and maturity levels in I4.0 MMs with reputable I4.0 RAMs to enhance strategy for I4.0 transformation and implementation.

Three steps of alignment consist of the systematic literature review (SLR) method to study the current published high-quality I4.0 MMs, the taxonomy development of I4.0 influencing factors by adapting and implementing the categorisation of system theories and aligning I4.0 MMs with RAMs.

The study discovered that different I4.0 MMs lead to varied organisational interpretations. Challenges and insights arise when aligning I4.0 MMs with RAMs. Aligning MM levels with RAM stages is a crucial milestone in the journey toward I4.0 transformation. Evidence indicates that I4.0 MMs and RAMs often overlook the cultural domain.

Findings contribute to the literature on aligning capabilities with implementation strategies while employing I4.0 MMs and RAMs. We use five RAMs (RAMI4.0, NIST-SME, IMSA, IVRA and IIRA), and as a common limitation in SLR, there could be a subjective bias in reading and selecting literature.

To fully leverage the capabilities of RAMs as part of the I4.0 implementation strategy, companies should initiate the process by undertaking a thorough needs assessment using I4.0 MMs.

The novelty of this paper lies in being the first to examine the alignment of I4.0 MMs with established RAMs. It offers valuable insights for improving I4.0 implementation strategies, especially for companies using both MMs and RAMs in their transformation efforts.