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This study aims to discuss the state-of-the-art digital factory (DF) development combining digital twins (DTs), sensing devices, laser additive manufacturing (LAM) and subtractive manufacturing (SM) processes. The current shortcomings and outlook of the DF also have been highlighted. A DF is a state-of-the-art manufacturing facility that uses innovative technologies, including automation, artificial intelligence (AI), the Internet of Things, additive manufacturing (AM), SM, hybrid manufacturing (HM), sensors for real-time feedback and control, and a DT, to streamline and improve manufacturing operations.

This study presents a novel perspective on DF development using laser-based AM, SM, sensors and DTs. Recent developments in laser-based AM, SM, sensors and DTs have been compiled. This study has been developed using systematic reviews and meta-analyses (PRISMA) guidelines, discussing literature on the DTs for laser-based AM, particularly laser powder bed fusion and direct energy deposition, in-situ monitoring and control equipment, SM and HM. The principal goal of this study is to highlight the aspects of DF and its development using existing techniques.

A comprehensive literature review finds a substantial lack of complete techniques that incorporate cyber-physical systems, advanced data analytics, AI, standardized interoperability, human–machine cooperation and scalable adaptability. The suggested DF effectively fills this void by integrating cyber-physical system components, including DT, AM, SM and sensors into the manufacturing process. Using sophisticated data analytics and AI algorithms, the DF facilitates real-time data analysis, predictive maintenance, quality control and optimal resource allocation. In addition, the suggested DF ensures interoperability between diverse devices and systems by emphasizing standardized communication protocols and interfaces. The modular and adaptable architecture of the DF enables scalability and adaptation, allowing for rapid reaction to market conditions.

Based on the need of DF, this review presents a comprehensive approach to DF development using DTs, sensing devices, LAM and SM processes and provides current progress in this domain.

In recent years, additive manufacturing (AM) technology has been acknowledged as an efficient method for producing geometrical complex objects with a wide range of applications. However, dimensional inaccuracies and presence of defects hinder the broad adaption of AM procedures. These factors arouse concerns regarding the quality of the products produced with AM and the utilization of quality control (QC) techniques constitutes a must to further support this emerging technology. This paper aims to assist researchers to obtain a clear sight of what are the trends and what has been inspected so far concerning non-destructive testing (NDT) QC methods in AM.

In this paper, a survey on research advances on non-destructive QC procedures used in AM technology has been conducted. The paper is organized as follows: Section 2 discusses the existing NDT methods applied for the examination of the feedstock material, i.e. incoming quality control (IQC). Section 3 outlines the inspection methods for in situ QC, while Section 4 presents the methods of NDT applied after the manufacturing process i.e. outgoing QC methods. In Section 5, statistical QC methods used in AM technologies are documented. Future trends and challenges are included in Section 6 and conclusions are drawn in Section 7.

The primary scope of the study is to present the available and reliable NDT methods applied in every AM technology and all stages of the process. Most of the developed techniques so far are concentrated mainly in the inspection of the manufactured part during and post the AM process, compared to prior to the procedure. Moreover, material extrusion, direct energy deposition and powder bed processes are the focal points of the research in NDT methods applied in AM.

This literature review paper is the first to collect the latest and the most compatible techniques to evaluate the quality of parts produced by the main AM processes prior, during and after the manufacturing procedure.

Inconsistencies in build quality part-to-part and build-to-build continue to be a problem in additive manufacturing (AM). The flexibility of AM often enables low-volume and custom production, making conventional methods of machine qualification and health monitoring challenging to implement. Machine health has been difficult to separate from the effects of design and process decisions, and therefore inferring machine health through part quality has been similarly complicated.

This conceptual paper proposes a framework for monitoring machine health by monitoring two types of witness parts, in the form of witness builds and witness artifacts, to provide sources of data for potential indicators of machine health.

The proposed conceptual framework with witness builds and witness artifacts permits the implementation into AM techniques to monitor machine health according to part quality. Subsequently, probabilistic models can be used to optimize machine costs and repairs, as opposed to statistical approaches that are less ideal for AM. Bayesian networks, hidden Markov models and Markov decision processes may be well-suited to accomplishing this task.

Though variations of witness builds have been created for use in AM to measure build quality and machine capabilities, the literature contains no previously proposed framework that permits the evaluation of machine health and its influence on quality through a combination of witness builds and witness artifacts, both of which can be easily added into AM production.

The smaller sizes of current electronic devices suggest the feasibility of creating a smart composite structure using piezoelectric implant to monitor in-situ and in-service conditions the life of civil and aerospace structures. Piezoelectric (lead zirconate-titanate (PZT)) sensors embedded within laminates composites represent a new branch of engineering with the potential to greatly enhance the confidence and use of these materials. The paper aims to discuss these issues.

This study presents a health monitoring of laminates composites materials incorporating by piezoelectric (PZT) implant using acoustic emission (AE) technique. A series of specimens of laminate composite with and without embedded piezoelectric were tested in three-point bending tests in static and creep loading while continuously monitoring the response by the AE technique. The AE signals were analysed using the classification k-means method in order to identify the different damages and to follow the evolution of these various mechanisms for both types of materials (with and without embedded sensors).

Comparing embedded sensor to sensor mounted on the surface, the embedded sensor showed a much higher sensitivity. It was thus verified that the embedded AE sensor had great potential for AE monitoring in fibre reinforced composites structures.

Piezoelectric implant to monitor in-situ and in-service conditions the life of civil and aerospace structures.

This paper seeks to present a prognostics approach using the Mahalanobis distance (MD) method to predict the reliability of multilayer ceramic capacitors (MLCCs) in temperature‐humidity‐bias (THB) conditions.

Data collected during THB testing of 96 MLCCs were analyzed using the MD method. In the THB tests, three parameters (capacitance (C), dissipation factor (DF), and insulation resistance (IR)) were monitored in situ. A Mahalanobis space (MS) was formed from the MD values of a set of non‐failed MLCCs. MD values for the remaining MLCCs were compared with an MD threshold. Data for MLCCs which exceeded the threshold were examined using the failure criteria for the individual electrical parameters to identify failures and precursors to failure.

It was found that the MD method provided an ability to detect failures of the capacitors and identify precursors to failure, although the detection rate was not perfect.

It was observed that the quality and construction of the MS, together with the choice of the MD threshold, were the critical factors determining the sensitivity of the MD method. Recommendations are offered for improved sensitivity to enable assessment of intermittent failures.

MD analysis of the multivariate MLCC data set illustrates how detection of failures can be simplified in a system for which several parameters were monitored simultaneously. This makes the MD method of great potential value in a health‐monitoring system.

Due to the complexity of and variations in additive manufacturing (AM) processes, there is a level of uncertainty that creates critical issues in quality assurance (QA), which must be addressed by time-consuming and cost-intensive tasks. This deteriorates the process repeatability, reliability and part reproducibility. So far, many AM efforts have been performed in an isolated and scattered way over several decades. In this paper, a systematically integrated holistic view is proposed to achieve QA for AM.

A systematically integrated view is presented to ensure the predefined part properties before/during/after the AM process. It consists of four stages, namely, QA plan, prospective validation, concurrent validation and retrospective validation. As a foundation for QA planning, a functional workflow and the required information flows are proposed by using functional design models: Icam DEFinition for Function Modeling.

The functional design model of the QA plan provides the systematically integrated view that can be the basis for inspection of AM processes for the repeatability and qualification of AM parts for reproducibility.

A powder bed fusion process was used to validate the feasibility of this QA plan. Feasibility was demonstrated under many assumptions; real validation is not included in this study.

This study provides an innovative and transformative methodology that can lead to greater productivity and improved quality of AM parts across industries. Furthermore, the QA guidelines and functional design models provide the foundation for the development of a QA architecture and management system.

This systematically integrated view and the corresponding QA plan can pose fundamental questions to the AM community and initiate new research efforts in the in-situ digital inspection of AM processes and parts.

The energy retrofit of the existing building stock, and specifically the thermal upgrading of the buildings’ envelopes, has been identified as a key action for both the decarbonisation of the built environment and the reduction in fuel poverty. When considering the energy retrofit of heritage buildings it is, however, important to recognise both the technical issues that this entails and the potential impact on their cultural value and the emotional responses to it. The purpose of this paper is to focus on the thermal upgrading of historic timber-framed buildings in the UK.

The paper begins by exploring the cultural significance of this form of building construction, before examining three case studies using both quantitative and qualitative methodologies.

The results show that whilst the application of energy retrofit actions to this emblematic typology may have limited success, the emotional connection of the buildings’ occupants often results in the work resulting in higher user satisfaction than would otherwise be expected.

Although limited in number, the three case studies provide an insight into the complex issues surrounding the low energy retrofit of historic timber-framed buildings. Further research into this area is encouraged.

The paper contains the monitoring of specific retrofit details, the results of which should inform future projects.

The review of the cultural significance of historic timber-frame buildings in the UK underlines the importance of the conservation and continuing survival of these buildings.

Previous heritage retrofit research in the UK has focussed on solid wall construction with little investigation into the issues surrounding the retrofit of historic timber-frame buildings. This paper explores this previously under-researched area. Additionally, this paper begins to explore the possible links between occupants’ emotional connection to historic buildings and their perceived levels of comfort.

The purpose of this paper is to further validate a wireless sensor system developed at Clarkson University for structural monitoring of highway bridges. The particular bridge monitored employs a fiber reinforced polymer (FRP) panel system which is fairly innovative in the field of civil engineering design. The superstructure was monitored on two separate occasions to determine a change in structural response and see how the structural system performs over time.

A series of wireless sensor units was deployed at various locations of the steel superstructure, to measure both the modal response from acceleration measurements as well as quasi‐static and dynamic strain response. Ambient and forced loading conditions were applied to measure the response. Data results were compared over two separate periods approximately nine months apart.

The first eight mode shapes were produced from output‐only system identification providing natural frequencies ranging from approximately 6 to 42 Hz. The strain response was monitored over two different testing periods to measure various performance characteristics. Neutral axis, distribution factor, impact factor and end fixity were determined. Results appeared to be different over the two testing periods. They indicate that the load rating of the superstructure decreased over the nine month period, possibly due to deterioration of the materials or composite action.

The results from the two testing periods indicate that further testing needs to be completed to validate the change in response. It is difficult to say with certainty that the significant change in response is due to bridge deterioration and not other factors such as temperature effects on load rating. The sensor system, however, proved to provide high quality data and responses indicating its successful deployment for load testing and monitoring of highway infrastructure.

The paper provides a depiction of the change in structural behavior of a bridge superstructure using a wireless sensor system. The wireless system provided high‐rate data transmission in real time. Load testing at two different points in time, eight months apart, showed a significant change in bridge behavior. The paper provides a practical and actual physical load test and rating during these two periods for quantifiable change in response. It is shown that the wireless system is capable of infrastructure monitoring and that possible deterioration is expected with this particular bridge design. Additionally, the load testing occurred during different seasons, which could create cause for temperature effects in load rating. This can provide a basis for future performance monitoring techniques and structural health monitoring.

The International Maritime Organization has decided that as of 1.1.2020, SOx content in a ship’s emissions should be no more than 0.5 per cent. The purpose of this paper is to address the various challenges expected to arise from the enforcement of the global cap sulfur regulation.

The authors outline various enforcement options and present a model that calculates the profits from noncompliance in the high seas, so as to help determine the level of fines that could be imposed in case of violation.

The main finding is that a harmonized system of fines, which are more than potential savings from cheating, would be a strong deterrent for compliance.

To the authors’ knowledge, no paper in the maritime literature on sulfur regulations has focused on enforcement as of yet.

The purpose of this study is the introduction and validation of a new technique for process monitoring during electron beam melting (EBM).

In this study, a backscatter electron detector inside the building chamber is used for image acquisition during EBM process. By systematic variation of process parameters, the ability of displaying different topographies, especially pores, is investigated. The results are evaluated in terms of porosity and compared with optical microscopy and X-ray computed tomography.

The method is capable of detecting major flaws (e.g. pores) and gives information about the quality of the resulting component.

Image acquisition by evaluating backscatter electrons during EBM process is a new approach in process monitoring which avoids disadvantages restricting previously investigated techniques.