Causal Discovery in Manufacturing: A Structured Literature Review

Industry 4.0 radically alters manufacturing organization and management, fostering collection and analysis of increasing amounts of data. Advanced data analytics, such as machine learning (ML), are essential for implementing Industry 4.0 and obtaining insights regarding production, better decision support, and enhanced manufacturing quality and sustainability. ML outperforms traditional approaches in many cases, but its complexity leads to unclear bases for decisions. Thus, acceptance of ML and, concomitantly, Industry 4.0, is hindered due to increasing requirements of fairness, accountability, and transparency, especially in sensitive-use cases. ML does not augment organizational knowledge, which is highly desired by manufacturing experts. Causal discovery promises a solution by providing insights on causal relationships that go beyond traditional ML’s statistical dependency. Causal discovery has a theoretical background and been successfully applied in medicine, genetics, and ecology. However, in manufacturing, only experimental and scattered applications are known; no comprehensive overview about how causal discovery can be applied in manufacturing is available. This paper investigates the state and development of research on causal discovery in manufacturing by focusing on motivations for application, common application scenarios and approaches, impacts, and implementation challenges. Based on the structured literature review, four core areas are identified, and a research agenda is proposed.

Modelling the Heating Process in the Transient and Steady State of an In Situ Tape-Laying Machine Head

As the use of composite materials increases, the search for suitable automated processes gains relevance for guaranteeing production quality by ensuring the uniformity of the process, minimizing the amount of scrap generated, and reducing the time and energy consumption. Limitations on production by traditional means such as hand lay-up, vacuum bagging, and in-autoclave methods tend not to be as efficient when the size and shape complexity of the part being produced increases, motivating the search for alternative processes such as automated tape laying (ATL). This work aims to describe the process of modelling and simulating a composite ATL with in situ consolidation by characterizing the machine elements and using the finite differences method in conjunction with energy balances in order to create a digital twin of the process for further control design. The modelling approach implemented is able to follow the process dynamics when changes are made to the heating element and to predict the composite material temperature response, making it suitable for use as a digital twin of a production process using an ATL machine.

Characterization of Wire-Bonding on LDS Materials and HF-PCBs for High-Frequency Applications

Thermosonic wire bonding is a well-established process. However, when working on advanced substrate materials and the associated required metallization processes to realize innovative applications, multiple factors impede the straightforward utilization of the known process. Most prominently, the surface roughness was investigated regarding bond quality in the past. The practical application of wire bonding on difficult-to-bond substrates showed inhomogeneous results regarding this quality characteristic. This study describes investigations on the correlation among the surface roughness, profile peak density and bonding quality of Au wire bonds on thermoplastic and thermoset-based substrates used for high-frequency (HF) applications and other high-end applications. FR4 PCB (printed circuit board flame resitant class 4) were used as references and compared to HF-PCBs based on thermoset substrates with glass fabric and ceramic filler as well as technical thermoplastic materials qualified for laser direct structuring (LDS), namely LCP (liquid crystal polymer), PEEK (polyether ether ketone) and PTFE (polytetrafluoroethylene). These LDS materials for HF applications were metallized using autocatalytic metal deposition to enable three-dimensional structuring, eventually. For that purpose, bond parameters were investigated on the mentioned test substrates and compared with state-of-the-art wire bonding on FR4 substrates as used for HF applications. Due to the challenges of the limited thermal conductivity and softening of such materials under thermal load, the surface temperatures were matched up by thermography and the adaptation of thermal input. Pull tests were carried out to determine the bond quality with regard to surface roughness. Furthermore, strategies to increase reliability by the stitch-on-ball method were successfully applied.

Significant Reduction in Energy Consumption and Carbon Emission While Improving Productivity in Laser Drilling of CFRP Sheets with a Novel Stepped Process Parameter Parallel Ring Method

Although laser drilling of carbon fibre-reinforced polymer (CFRP) composites offers the advantages of zero tool-wear and avoidance of fibre delamination compared with mechanical drilling, it consumes considerably more energy during the drilling process. This research shows that by using a new, stepped parameter parallel ring laser hole drilling method, an energy saving of 78.10% and an 18.37 gCO2 reduction for each hole, while improving productivity by more than 300%, can be achieved in laser drilling of 6 mm diameter holes in CFRP sheets of 2 mm in thickness, compared with previous laser drilling methods under the same drilling quality. The key reason for this is an increase in energy input to the inner rings enabling more rapid removal of the material, while the lower energy input for the outer ring provides a shielding trench to reduce the heat loss into the parent material. The results are compared with single-ring laser drilling and multiple-ring laser drilling with constant processing parameters, and a discussion is given on comparing with mechanical drilling and future prospects, including a combined mechanical drilling and laser pre-scribing process.

Development and Evaluation of the Ultrasonic Welding Process for Copper-Aluminium Dissimilar Welding

The demand for joining dissimilar metals has exponentially increased due to the global concerns about climate change, especially for electric vehicles in the automotive industry. Ultrasonic welding (USW) surges as a very promising technique to join dissimilar metals, providing strength and electric conductivity, in addition to avoid metallurgical defects, such as the formation of intermetallic compounds, brittle phases and porosities. However, USW is a very sensitive process, which depends on many parameters. This work evaluates the impact of the process parameters on the quality of ultrasonic spot welds between copper and aluminium plates. The weld quality is assessed based on the tensile strength of the joints and metallographic examination of the weld cross-sections. Furthermore, the welding energy is examined for the different welding conditions. This is done to evaluate the influence of each parameter on the heat input resulting from friction at the weld interface and on the weld quality. From the obtained results, it was possible to optimise parameters to achieve satisfactory weld quality in 1.0 mm thick Al–Cu plate joints in terms of mechanical and metallurgical properties.

Review on Additive Manufacturing of Multi-Material Parts: Progress and Challenges

Additive manufacturing has already been established as a highly versatile manufacturing technique with demonstrated potential to completely transform conventional manufacturing in the future. The objective of this paper is to review the latest progress and challenges associated with the fabrication of multi-material parts using additive manufacturing technologies. Various manufacturing processes and materials used to produce functional components were investigated and summarized. The latest applications of multi-material additive manufacturing (MMAM) in the automotive, aerospace, biomedical and dentistry fields were demonstrated. An investigation on the current challenges was also carried out to predict the future direction of MMAM processes. It was concluded that further research and development is needed in the design of multi-material interfaces, manufacturing processes and the material compatibility of MMAM parts.

Influence of Surface Preparation on Cracking Phenomena in TIG-Welded High and Medium Entropy Alloys

Multi-element systems with defined entropy (HEA—high entropy alloy or MEA—medium entropy alloy) are rather new material concepts that are becoming increasingly important in materials research and development. Some HEA systems show significantly improved properties or combinations of properties, e.g., the overcoming of the trade-off between high strength and ductility. Thus, the synthesis, the resulting microstructures, and properties of HEA have been primarily investigated so far. In addition, processing is crucial to achieve a transfer of potential HEA/MEA materials to real applications, e.g., highly stressed components. Since fusion welding is the most important joining process for metals, it is of vital importance to investigate the weldability of these materials. However, this has rarely been the subject of research to date. For that reason, in this work, the weldability depending on the surface preparation of a CoCrFeMnNi HEA and a CoCrNi MEA for TIG welding is investigated. The fusion welding of longer plates is described here for the first time for the CoCrNi alloy. The welds of both materials showed distinct formation of cracks in the heat affected zone (HAZ). Optical and scanning electron microscopy analysis clearly confirmed an intergranular fracture topography. However, based on the results, the crack mechanism cannot be conclusively identified as either a liquid metal embrittlement (LME) or hot cracking-like liquid film separation.

Development of a Low-Cost Wire Arc Additive Manufacturing System

Due to their unique advantages over traditional manufacturing processes, metal additive manufacturing (AM) technologies have received a great deal of attention over the last few years. Using current powder-bed fusion AM technologies, metal components are very expensive to manufacture, and machines are complex to build and maintain. Wire arc additive manufacturing (WAAM) is a new method of producing metallic components with high efficiency at an affordable cost, which combines welding and 3D printing. In this work, gas tungsten arc welding (GTAW) is incorporated into a gantry system to create a new metal additive manufacturing platform. Design and build of a simple, affordable, and effective WAAM system is explained and the most frequently seen problems are discussed with their suggested solutions. Effect of process parameters on the quality of two additively manufactured alloys including plain carbon steel and Inconel 718 were studied. System design and troubleshooting for the wire arc AM system is presented and discussed.

Multi-Scale Modeling of Residual Stresses Evolution in Laser Powder Bed Fusion of Inconel 625

Laser powder bed fusion exhibits many advantages for manufacturing complex geometries from hard to machine alloys such as IN625. However, a major drawback is the formation of high tensile residual stresses, and the complex relationship between the process parameters and the residual stresses has not been fully investigated. The current study presents multi-scale models to examine the variation of process parameters on melt pool dimensions, cyclic temperature evolutions, cooling rate, and cyclic stress generation and how they affect the stress end state. In addition, the effect of the same energy density, which is often overlooked, on the generated residual stresses is investigated. Multi-level validation is performed based on melt pool dimensions, temperature measurements with a two-color pyrometer, and finally, in-depth residual stress measurement. The results show that scan speed has the strongest effect on residual stresses, followed by laser power and hatch spacing. The results are explained in light of the non-linear temperature evolution, temperature gradient, and cooling rate during laser exposure, cooling time, and the rate during recoating time.

Laser Scanning Based Object Detection to Realize Digital Blank Shadows for Autonomous Process Planning in Machining

The automated process chain of an unmanned production system is a distinct challenge in the technical state of the art. In particular, accurate and fast raw-part recognition is a current problem in small-batch production. This publication proposes a method for automatic optical raw-part detection to generate a digital blank shadow, which is applied for adapted CAD/CAM (computer-aided design/computer-aided manufacturing) planning. Thereby, a laser-triangulation sensor is integrated into the machine tool. For an automatic raw-part detection and a workpiece origin definition, a dedicated algorithm for creating a digital blank shadow is introduced. The algorithm generates adaptive scan paths, merges laser lines and machine axis data, filters interference signals, and identifies part edges and surfaces according to a point cloud. Furthermore, a dedicated software system is introduced to investigate the created approach. This method is integrated into a CAD/CAM system, with customized software libraries for communication with the CNC (computer numerical control) machine. The results of this study show that the applied method can identify the positions, dimensions, and shapes of different raw parts autonomously, with deviations less than 1 mm, in 2.5 min. Moreover, the measurement and process data can be transferred without errors to different hardware and software systems. It was found that the proposed approach can be applied for rough raw-part detection, and in combination with a touch probe for accurate detection.