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In recent years, the evolution of computer-aided design technology has established a new design method to improve digital model creations. The new design method is called Parametric Modeling. In this paper, 3D metallic models are printed using a novel Parametric Modeling approach. The goal of this approach is to use parametric design features to simulate and print 3D metallic objects using Laser Wire Additive Manufacturing (LWAM) process. The proposed approach includes a pattern creation and robot targets assignment while considering several process requirements of LWAM and the robot system. This technique will allow the development of an adaptive robot toolpath for a good deposition process. Finally, a wall, a cylinder, and a complex shape were simulated and deposited to validate the proposed approach. The results show that the approach is feasible, adaptive, and can enhance 3D metallic print in the LWAM process.

Variations in quantities, qualities and time availability of input materials pose a major risk to circular supply chains (CSC) and require new models for creating and evaluating adaptive and resilient CSC in the circular economy (CE). This can be achieved by consistently modelling the overarching relationship between resource input- and output streams, without neglecting the associated risks. The model proposed below consists of five components which are based on five resilience requirements for SCs and provides a data-based recommended course of action for managers at a low entry-barrier. It consists of a CSC visualization, a safety stock calculation, a risk monitoring for each SC node, a reporting logic, and a measurement catalogue. The inspiration for this model came from an innovative case study (“Zirkelmesser”) in the metal processing industry in which secondary products and materials are used to produce new products. Here, the problem of maintaining the resource supply arose and led to resilience issues. The mentioned case study is used as an application example for the model application and helps to make emerging circular supply chains predictable and better manageable, thus increasing their resilience.

Laser joining of polymers to metals is a rising research subject due to the potential of considerably reducing the weight of structures. This article deals with the laser joining process between polypropylene and aluminum. Without pre-treatment, laser joining of these materials is not feasible, and the method applied in this study to circumvent this issue is a surface modification of aluminum with a pulsed laser to create mechanical interlocking for the heat conduction laser joining technique. Different patterns and various laser parameters are analyzed with the design of experiments to best understand the effects of each parameter along with microscopic observations. It is found that engraving weakens the mechanical properties of the aluminum samples. The compromise between the engraving depth and the mechanical properties of the samples is optimized, and the engraving process with a 0.28 mm line width, 27.3% density and 150 mm/s speed provides the highest mechanical performance of the assembly with minimum degradation of aluminum samples. Moreover, by adjusting the laser power and using power modulation below 300 W, the decomposition of polypropylene occurring at high temperatures is reduced to a minimum. After the final optimization, the joined samples reliably withstand a maximum force of 1500 N, which is, approximately, a shear strength of 20 MPa.

The concept of Circular Economy (CE) is gaining increasing attention as an indispensable renewal of linear economy without neglecting sustainable development goals. Closing resource loops and keeping resources in the system at the highest level of use for as long as possible are cited as the main goals of CE. However, due to missing information exchange, the lack of consistency between the existing end-of-life (EOL) infrastructure and the respective product designs hinders a successful circularity of resources. This research presents a method to collect, process, and apply EOL process data to provide the beginning-of-life (BOL) with important EOL-knowledge through a CE-adapted product design assessment. EOL-data is collected using a Circular Value Stream Mapping (C-VSM), EOL-information is processed using a digital state flow representation, and EOL-knowledge is applied by providing a decision-support tool for product designers in the context of a PET bottle case study in Luxembourg. The goal is to anticipate a circular flow of resources by reflectively aligning product design with the relevant EOL infrastructure. In contrast to the linear economy, the developed method makes it possible to consider not only the requirements of users but also the actual end users, the EOL process chains, when designing products.

Nowadays, hybrid polymer/metal assemblies experience a growing demand in the industry, especially for transports and biomedical purposes. Those assemblies offer many advantages, such as lightweight structures and corrosion resistance. The main difficulty to assemble them remains. In this sense, laser welding is more than a promising technique because of its rapidity, the absence of intermediate materials, and its high design freedom. Unfortunately, several fundamental aspects are not well understood yet, as the chemical bonding at the interface. For this work, common materials are studied: polyamide-6.6 and aluminum. A previous published work strongly suggests the formation of a C-O-Al bond at the interface, but this information needs to be confirmed and the reaction mechanism is still uncertain. To achieve this goal, two different model samples were prepared. The first ones are spin-coated layers of polyamide-6.6 on mirror polished aluminum; the other samples are made of a layer of N-methylformamide mimicking the reactive part of the polymer, dip-coated on aluminum. Both sample types were analyzed with XPS and ToF-SIMS and display similar results: C-O-Al bond formation at the interface is confirmed and a reaction mechanism is proposed.

Laser welding of copper to aluminum is challenging due to the formation of complex intermetallic phases. More Al (~18.5 at. %) can be dissolved in Cu, in contrast to Cu (~2.5 at. %) in Al. Therefore, welding from copper side, large melting of Al can be achieved. However optimum Cu and Al must be melted for a strong joint. Finding the right amount is difficult and time consuming by tradition analysis technique like inspection by weld cross-sections. Considering the speed of the welding process and complexity of analysis involving with metallography cross-sections, alternative rapid method to qualify the welds are necessary. The acoustic emission during laser welding can give proportional information of the Al, Cu melted. With such an approach the weld status can be obtained in real time. In this paper the acoustic welding signal using an airborne sensor in the audible range of 20 Hz to 20 kHz, is correlated to the weld strength and material mixing (Al, Cu melt). Finally, the weld status is predicted by an artificial neural network based on the acquired signal.

Augmented reality (AR) is a technology that allows overlaying of virtual elements on top of the physical environment. This enhances the perception and conveys additional information to the user. With the emergence of industry 4.0 concepts in manufacturing landscape, AR found its way to improve existing Human-Machine Interfaces (HMI) on the shop-floor. The industrial setting has a wide variety of application opportunities from AR, ranging from training and digital work instructions to quality inspection and remote maintenance. Even though its implementation in the industry is rising in popularity, it is still mainly restricted to large companies due the limited availability of resources in Small and Medium Size Enterprises (SME). However, SMEs can benefit from AR solutions in its production processes. Therefore, this research aims to develop and present the results of comparison of two simple and cost-effective AR software frameworks for Hand Held Device (HHD) and a Head Mounted Device (HMD), which can be applied for developing AR applications for manufacturing. Two AR applications are developed using these software frameworks which are presented in the case study section. Android device is chosen as a HHD and HoloLens is the HMD used in the case study. The development structure can be reproduced by a wider range of enterprises with diverse needs and resource availability.

There has been a rapid increase in the use of collaborative robots in manufacturing industries within the context of Industry 4.0 and smart factories. The existing human–robot interactions, simulations, and robot programming methods do not fit into these fast-paced technological advances as they are time-consuming, require engineering expertise, waste a lot of time in programming and the interaction is not trivial for non-expert operators. To tackle these challenges, we propose a digital twin (DT) approach for human–robot interactions (HRIs) in hybrid teams in this paper. We achieved this using Industry 4.0 enabling technologies, such as mixed reality, the Internet of Things, collaborative robots, and artificial intelligence. We present a use case scenario of the proposed method using Microsoft Hololens 2 and KUKA IIWA collaborative robot. The obtained results indicated that it is possible to achieve efficient human–robot interactions using these advanced technologies, even with operators who have not been trained in programming. The proposed method has further benefits, such as real-time simulation in natural environments and flexible system integration to incorporate new devices (e.g., robots or software capabilities).

Polymer/metal hybrid assemblies are well suited for automotive and biomedical applications because of their ability to create lightweight structures with a wide range of design possibilities. Laser welding is a promising technique for joining dissimilar materials thanks to its quickness, freedom of design and absence of adhesives. Still, the fundamental causes of adhesion in hybrid laser welding remain not well understood. Therefore, the present work aims at highlighting a chemical bonding between a polymer, nylon-6.6, and a metal, aluminum. To access the interface information, the samples were first broken, leaving a residue on the surface, which was dissolved afterward. The chemical reactive sites of the nylon molecule able to react with aluminum surface were suggested and the feasibility of these reactions was analyzed in light of the results obtained by means of X-ray photoelectron spectroscopy (XPS) and time of flight secondary electron microscopy (ToF-SIMS).

Laser-assisted metal–polymer joining (LAMP) is a novel assembly process for the development of miniaturized joints in hybrid lightweight products. This work adopts a design of experiments (DoE) approach to investigate the influence of several laser welding parameters on the strength and quality of titanium alloy (Ti-6Al-4V)–polyamide (PA6.6) assembly. Significant parameters were highlighted using the Plackett Burmann design, and process window was outlined using the Response Surface Method (RSM). A statistically reliable mathematical model was generated to describe the relation between highlighted welding parameters and joint strength. The analysis of variance (ANOVA) method was implemented to identify significant parametric interactions. Results show the prominence of focal position and laser power, as well as significant interaction between laser power and beam speed, on the joint strength. The evolution of weld defects (bubbles, excessive penetration, flashing, titanium coloring, weld pool cavities, and welding-induced deflection) along the process window was investigated using optical microscopy. The resulted deflection in titanium was quantified, and its relationship with welding parameters was mathematically modeled. Robust process window was outlined to maintain insignificant deflection in the welded joints. Results showed that the growth of weld defects correlates with a decline in joint strength. Optimal parameters demonstrated a defect-free joint, maximizing joint strength.

The laser polishing surface treatment is a prerequisite for enhanced weldability that is enabled by superior adhesion between the weldments. The paper describes the laser polishing process of the aluminum surface to develop a relatively thick and porous artificial aluminum oxide layer. Microscopic observation shows the laser polishing process significantly improves the adhesion of molten polyamide to the aluminum surface. Besides, the shear load of the pretreated joints is much higher than that of as-received ones. However, for the majority of the welded samples, the failure happens at the polyamide near the interface of aluminum/polyamide due to the thermal effect and structural changes of polyamide during the welding process. By applying the post-treatment of the welded specimens with different cycles, the mentioned failure mechanism is not observed anymore. Therefore, the mechanical properties of the joint will be improved and reach to the limits of the base materials.

As far as complex contact-based manufacturing tasks are concerned, humans outperform machines. Indeed, conventionally controlled robotic manipulators are limited to basic applications in close to ideal circumstances. However, tedious work in hazardous environments, make some tasks unsuitable for humans. Therefore, the interest in expanding the application-areas of robots arose. This paper employs a bottom-up approach to develop robust and adaptive learning algorithms for trajectory tracking: position and torque control in the presence of uncertainties and switching constraints. The robotic manipulators mimicking the human behavior based on bio-inspired algorithms, take advantage of their know-how. Simulations and experiments validate the concept-performance.

Improving the vibration isolation for the seat of small vehicles under low excitation frequencies is important for providing good comfort for the driver and passengers. Thus, in this study, a compact, low-dynamic, and high-static stiffness vibration isolation system has been designed. A theoretical analysis of the proposed quasi-zero stiffness (QZS) isolator system for vehicle seats is presented. The isolator consists of two oblique springs and a vertical spring to support the load and to achieve quasi-zero stiffness at the equilibrium position. To support any additional load above the supported weight, a sleeve air spring is used. Furthermore, the two oblique springs are equipped with a horizontal adjustment mechanism that is aimed to reach higher frequencies with the existed stroke when a heavy load is applied. The proposed system can be fitted for small vehicles, especially for B-segment and C-segment cars. Finally, the simulation results reveal that the proposed system has a large isolation frequency range compared to that of the linear isolator.

Since the mitigation of climate change is one of the biggest challenges to face on a global scale, the topic has become more relevant also in industrial context. Learning factories have proven to be suitable environments to address and convey competencies to tackle industrial challenges in an interactive way. Hence, several learning factories are already dealing with sustainability topics in various use cases. This paper strives to present a state of the art of sustainability and circular economy in learning factories. Therefore, a classification framework is developed based on the state of the art of several learning factories and existing literature regarding the topic. This framework is then used to systematically describe the different activities regarding sustainability and circular economy that are currently ongoing in learning factories worldwide. This can be used to get an idea about the different aspects of the topic and how to address them, but furthermore also offers assistance to identify “blind spots” which could and should be addressed in learning factories in the future.

Laser Wire-Feed Metal Additive Manufacturing (LWAM) is a process that utilizes a laser to heat and melt a metallic alloy wire, which is then precisely positioned on a substrate, or previous layer, to build a three-dimensional metal part. LWAM technology offers several advantages, such as high speed, cost effectiveness, precision control, and the ability to create complex geometries with near-net shape features and improved metallurgical properties. However, the technology is still in its early stages of development, and its integration into the industry is ongoing. To provide a comprehensive understanding of the LWAM technology, this review article emphasizes the importance of key aspects of LWAM, including parametric modeling, monitoring systems, control algorithms, and path-planning approaches. The study aims to identify potential gaps in the existing literature and highlight future research opportunities in the field of LWAM, with the goal of advancing its industrial application.

In laser wire Additive manufacturing (LWAM), the final geometry is produced using layer-by-layer deposition principle of beads. To achieve good geometrical accuracy of the final product, proper implementation of the bead geometry is essential. The process parameters have a direct influence on the bead geometry, thus to the printed part. In this paper, we propose a bead width prediction model to improve deposition accuracy. A regression algorithm is applied to the experimental results to predict the bead width dimension. Bead prediction equation relating the bead width growth for each layer is obtained for a given set of process parameters. The prediction equations show similar evolution trends and confirm the influence of deposition process parameters on the bead width. The proposed method demonstrates a prospective insight on a more proper selection of process or physical parameter intervening in laser wire additive manufacturing process.

The Circular Economy (CE) concept aims to close resource loops and keep resources in the system for as long as possible at the highest utility level, without neglecting the goals of sustainable development. This paradigm shift from a finite and linear to a circular economy is however only possible if systems can be viewed as holistic overall systems. Thus, preventive problems can be identified and located as early as possible and counteracting measures initiated. This paper presents a new value stream mapping (VSM) model to consider interrelated processes in a holistic manner, regarding the requirements of CE. To do so, one macro-level to consider interrelated company relationships together with a respective micro-level to consider the individual company specific processes are elaborated. The degree of circularity is determined based on the 9R framework and new visualizations and measurement indicators are added at the different levels. This new model helps to mainly identify hurdles at a product's end-of-life, which are preventing a circular flow of resources, worth sharing with the responsible of a product's beginning-of-life. The model itself is validated by an extensive cross-company PET-bottle case study in Luxembourg.

In laser joining of copper (Cu) and aluminum (Al) sheets, the Al sheet is widely chosen as the top surface for laser irradiation because of increased absorption of laser beam and lower melting temperature of Al in contrast to Cu. This research focus on welding from Cu side to Al sheet. The main objective of irradiating the laser beam from the copper side (Cu on top) is to exploit higher solubility of Al in Cu. A significantly lower laser power can be used with 515 nm laser in comparison to 1030 nm. In addition to low laser power, a stable welding is obtained with 515 nm. Because of this advantage, 515 nm is selected for the current research. By fusion of Cu and Al the two sheet metals are welded, with presence of beneficial Cu solid solution phase and Al+Al2Cu in the joint with the brittle phases intermixed between the ductile phase. Therefore the mixed composition strengthens the joint. However excessive mixing leads to formation of more detrimental phases and less ductile phases. Therefore optimum mixing must be maintained. Energy dispersive X-ray spectroscopy (EDS) analysis indicate that large amount of beneficial Cu solid solution and Al rich phases is formed in the strong joint. From the tensile shear test for a strong joint, fracture is obtained on the heat-affected zone (HAZ) of Al. Therefore the key for welding from copper side is to have optimum melt with beneficial phases like Cu and Al+ Al2Cu and the detrimental phases intermixed between the ductile phases

The concept of the circular economy (CE) is receiving encouraging attention among scholars and practitioners, as a convenient solution to move away from the linear economy concept without neglecting the goals of sustainable development. The main goals of the CE are the closing of resource loops and the keeping of resources in the system for as long as possible at the highest utility level. However, as a result of the lack of internationally accepted definitions of the CE and several unsolved barriers, an excessive and inconsistent number of different CE applications exist. Most fields are mainly focusing on making a linear system circular instead of applying the CE principles in a holistic way. This paper presents a strategy to close the mentioned inconsistency gap, by contrasting currently discussed CE barriers and goals and thereof deriving two areas with a need for action (1. identifying the needed collection, sorting, and recovery infrastructure, and 2. developing circular product design guidelines). The strategy itself consists of connecting these two areas through an improved information exchange between the end-of-life (EOL) and beginning-of-life (BOL) of products. The result is CE design guidelines which are in accordance with the available or needed collection, sorting, and recovery infrastructure. The proposed strategy presents an innovative solution to apply CE principles in a holistic manner, based on EOL-driven product design.

Dissimilar metal joining of thin copper and aluminum sheets is very important in the battery connections. The main problem while joining this dissimilar combination is formation of brittle intermetallic phases that degrade the electrical and mechanical properties of the joint. For joining copper and aluminum sheet with laser, very high intensity in the range of 107 W/cm2 is required. Intermixture of copper and aluminum is vital for joint ductility. In this paper, the effect of combined oscillation and shaping of the laser pulses on the overlap welding of copper-aluminum is studied. Precise control of intermixing can be achieved by modifying the laser pulse i.e. the percentage of power with respect to the pulse time. Investigation on different pulse shapes with ramp up and ramp down profile is conducted by cross-section and microstructural analysis.

Quantifying lean and ICT architecture related to Industry 4.0 is a new challenge in Small and Medium Scale Enterprises (SMEs) that needs to be addressed by both research as well as enterprises themselves. Especially in the manufacturing sector, SMEs need to transform themselves into emerging trends such as industry 4.0 while practicing existing manufacturing philosophies such as Lean Production Systems (LPS) to be competitive in global markets. The major concern is that there are many assessment models available to measure the status of an enterprise related to either LPS or Industry 4.0. Often, these models are complex and don’t fulfill the requirements of manufacturing SMEs. On the other hand, most of the models only consider either lean or industry 4.0 elements. The outcomes of this research help to develop a hybrid model including both lean and industry 4.0 features suitable for manufacturing SMEs. The main objective of this research is to provide state of the art literature on existing assessment models and consequently map lean and industry 4.0 components to the specific characteristics of manufacturing SMEs. The paper concludes with a summary and outlook for our future research.

With the advent of Industry 4.0, manufacturing lines have evolved from processing goods in a serial manner to doing so by means of cellular manufacturing. Furthermore, the use of ubiquitous radio-frequency identification tags and cyber-physical systems allow to seamlessly follow goods through the manufacturing plant. The data collected from these can easily be used to abstract manufacturing networks as a directed graph with workstations as nodes and material flows as edges. It is also possible to analyze manufacturing networks in the sense of "flow networks" in order to answer questions about material flows. In a flow network, materials with different levels of processing move through the system from a source (the raw materials storage room, for example) to a sink (like a warehouse for finished goods). Raw materials leave the source at some steady rate, and finished goods arrive to the sink at the same rate. Directed edges act as conduits for material with a stated capacity and vertices (workstations) act as junctions where material flows without accumulating. The present work aims at solving the following optimization problem: given a manufacturing flow network of known edge capacities, determine the theoretical maximum production rate that the network can attain under the assumptions of steady state flow and zero intermediate inventory levels. To accomplish this, the manufacturing network must be analyzed in terms of complex networks and graph theory and the results subsequently interpreted in terms of Operations Research. Finally, the method is illustrated with the analysis of the manufacturing network of an appliances manufacturer by determining the maximum theoretical production rate and the network bottleneck.

Laser welding of metals – polymers has gained strong scientific and industrial interest because of its ability to produce miniaturized joints in lightweight products with customized properties. Surface pretreatments before joining process have shown significant impact on enhancing properties of laser welded metal – polymer joints. This work adopts a Design of Experiments (DoE) approach to investigate the influence of titanium alloy (Ti64) laser ablation parameters on the performance of laser welded Ti64 – polyamide (PA6.6) assemblies. In this first study, significant laser ablation parameters were highlighted, process window outlined, and optimal parameters identified. Laser ablation pretreatment parameters demonstrated a strong influence on joint resistance to failure. Effects of laser ablation parameters on titanium surface morphology were analyzed using Scanning Electron Microscope (SEM). In a second study, the effects of ablation parameters on Ti64 surface properties and welding quality will be investigated.

Augmented Reality (AR) systems have seen a rapid adaptation in both training and in virtual assembly instructions. AR systems assist the operator by enhancing user perception of reality, reducing the defects, and lead-time. However, there is a significant lack in the existing literature to compare AR systems and conventional work instructions. The aim of this research is to provide an empirical evidence of comparing task completion time, number of errors, workload index and system usability of AR and conventional paper-based work instructions. For this purpose, we designed an experiment where participants use paper based instructions and AR instructions to assemble a planetary gearbox. The task was assessed using NASA-TLX and System Usability Scale (SUS) tests, which allowed further analysis using descriptive statistics. Moreover, the qualitative interview at the end of the experiment gave more insights about participant’s overall experience.

The concept of circular economy (CE) aims to close and slow resource loops without neglecting the goals of sustainable development. Recently, the concept received encouraging attention among researchers and business experts to be a convenient solution to move away from the finite linear economy concept to a more sustainable solution. However, this change of paradigm is only possible if we consider systems in a holistic manner and can localize the preventing hurdles.

Increased customization and shortening product life cycles pose a challenge for automation, especially in assembly. In combination with the nature of assembly tasks, which may require high level of perception, skill, and logical thinking, these tasks are often conducted manually, especially in certain industries (e.g. furniture, power tools) or small and medium-sized enterprises. One of such tasks is the liquid level monitoring in gluing processes. Existing non-manual solutions are based on conventional and less flexible algorithms to detect the current liquid level. In production environments with highly individualized products, a need for more performant models arises. With artificial intelligence (AI) it is possible to deduct decisions from unknown multidimensional correlations in sensor data, which is a key enabler for assembly automation for products with high degree of customization.

Laser Wire Additive Manufacturing (LWAM) is a flexible and fast manufacturing method used to produce variants of high metal geometric complexity. In this work, a physics-based model of the bead geometry including process parameters and material properties was developed for the LWAM process of large-scale products. The developed model aimed to include critical process parameters, material properties and thermal history to describe the relationship between the layer height with different process inputs (i.e., the power, the standoff distance, the temperature, the wire-feed rate, and the travel speed). Then, a Model Predictive Controller (MPC) was designed to keep the layer height trajectory constant taking into consideration the constraints faced in the LWAM technology. Experimental validation results were performed to check the accuracy of the proposed model and the results revealed that the developed model matches the experimental data. Finally, the designed MPC controller was able to track a predefined layer height reference signal by controlling the temperature input of the system.

With the advent of Industry 4.0, manufacturing networks are increasingly flexible. However, a means to measure the potential level of flexibility as well as the practically attained one is missing. In this work, production lines are abstracted as directed complex networks and are evaluated using path-transfer flow entropy. Firstly, the path probability distribution of the binary representation of the manufacturing network is used to determine the level of flexibility that a production network can potentially achieve. Then, the weighted representation is employed to illustrate the degree of flexibility displayed in practice. A case study demonstrates the use of this technique and highlights practical limitations.

Nowadays, students struggle with understanding complex production processes and kinematics of machine tools and robots. While professors mostly have been dealing with these subjects for many years, students have only short time to be introduced to the complex nature of these topics. Mixed Reality allows students to engage hands-on in their subjects to reach new dimensions of understanding. Making challenging topics for students accessible by creating a more visual and tactile experience. The applications for entertainment and gaming are off the charts, but the implications for augmented reality in education and science are also undoubtedly massive. The project focusses on making education as interactive as possible, which helps both, teachers and students receive a unique tool for communicating phenomena and processes that are difficult to describe verbally. As a result, a complex knowledge becomes simple, an involvement of students grows, the quality of education increases

Information entropy metrics have been applied to a wide range of problems that were abstracted as complex networks. This growing body of research is scattered in multiple disciplines, which makes it difficult to identify available metrics and understand the context in which they are applicable. In this work, a narrative literature review of information entropy metrics for complex networks is conducted following the PRISMA guidelines. Existing entropy metrics are classified according to three different criteria: whether the metric provides a property of the graph or a graph component (such as the nodes), the chosen probability distribution, and the types of complex networks to which the metrics are applicable. Consequently, this work identifies the areas in need for further development aiming to guide future research efforts.

Motivated by high ecological and economical potentials and driven by new laws, remanufacturing is receiving increasing attention as a process that puts used products into “as good as new or better” condition. Within this process, there are many challenges, which are unseen in manufacturing, such as the uncertainties resulting from unknown conditions of the used products. This places special demands on the control of the remanufacturing system (RS). To handle these uncertainties an agent-based hybrid control architecture comprising centralized and decentralized components is presented. In the former, the scheduling takes place including the consideration of the use of automated guided vehicles (AGV) to realize flexible material handling within the RS. The scheduling of machines and AGVs is thereby considered simultaneously and not separately, as it is the case in currently available control systems. For the optimization of the simultaneous scheduling Constraint Programming (CP) is used. In the decentralized component, all participants within the RS will be networked as a cyber-physical system and controlled by respective agents. These agents can communicate with each other in order to find solutions. The architecture is implemented as a multi-agent system. Simulation results, using benchmark instances, show that simultaneous scheduling results in a 19.7% reduction of the makespan. Furthermore, the CP-based approach delivers the best results, compared to other approaches for simultaneous scheduling, which are also achieved in a significantly shorter computing time.

The main objectives of this chapter are to elucidate the necessity of a standardized value stream management (VSM) and to clarify how this standard can effectively increase corporate performance within cross-enterprise supply chain networks (SCNs). VSM is an effective tool to collect, evaluate, and continuously improve product and information flows within companies in a common and standardized manner. The findings of this chapter are not only valid for consistent product and information flows but are representative for the relevance of standards in general. In a globalized economy, standards need to be generally accepted and valid for all countries. Thus, corporate or national standards only have limited impact. The International Standardization Organization (ISO) provides the means to develop, negotiate and communicate standards, which are globally binding. This chapter shares the experience of ISO 22468 standard development within ISO/TC 154 WG7 and proves its applicability by an administrative use case.

In the present study, the laser welding of wire to flat geometry for miniature electromechanical hybrid components has been investigated. Considering the geometry of parts to be welded and also requirement of mechanical properties, spatial modulation of the laser beam was needed to be implemented to achieve a sound joint. Tensile-shear test and optical microscopy were employed to represent the mechanical properties and melt pool geometry of the joints. All welds were done by power modulation of the laser beam to better control the energy input at several feed rates and three different beam trajectories. Results showed that the shear load of the joint could be controlled by feed rate and the trajectory of the laser beam. Considering the material combination of the study that were nickel and CuSn6 bronze, which represented solubility in solid state, a joint stronger than base wire metal was achieved by defining a proper spatial modulation and feed rate of the laser beam.

With the advent of Industry 4.0, a growing number of sensors within modern production lines generate high volumes of data. This data can be used to optimize the manufacturing industry in terms of complex network topology metrics commonly used in the analysis of social and communication networks. In this work, several such metrics are presented along with their appropriate interpretation in the field of manufacturing. Furthermore, the assumptions under which such metrics are defined are assessed in order to determine their suitability. Finally, their potential application to identify performance limiting resources, allocate maintenance resources and guarantee quality assurance are discussed.

This paper presents the characterization of the intermetallic phases of laser-welded Al-Cu joints by synchrotron trough-the-substrate microdiffraction combined with SEM/EDX and etched/non-etched optical micrographs. Transmission microdiffraction offers the spatial resolution and beam flux necessary to study the intermetallic phases, which in conjunction with the excellent contrast of etched micrographs, rendered possible the phase identification. It was found that the major phases are Al2Cu (θ), Al4Cu9 (γ1) and AlCu (η2) were formed. The Al3Cu4 (ζ1) and δ phases where formed in less amount and found to be the primary cause for cracks inside the weld seam and therefore for the failure of the joint.

In Laser Wire Additive Manufacturing (LWAM), the final geometry is produced using the layer-by-layer deposition (beads principle). To achieve good geometrical accuracy in the final product, proper implementation of the bead geometry is essential. For this reason, the paper focuses on this process and proposes a layer geometry (width and height) prediction model to improve deposition accuracy. More specifically, a machine learning regression algorithm is applied on several experimental data to predict the bead geometry across layers. Furthermore, a neural network-based approach was used to study the influence of different deposition parameters, namely laser power, wire-feed rate and travel speed on bead geometry. To validate the effectiveness of the proposed approach, a test split validation strategy was applied to train and validate the machine learning models. The results show a particular evolutionary trend and confirm that the process parameters have a direct influence on the bead geometry, and so, too, on the final part. Several deposition parameters have been found to obtain an accurate prediction model with low errors and good layer deposition. Finally, this study indicates that the machine learning approach can efficiently be used to predict the bead geometry and could help later in designing a proper controller in the LWAM process.

The development of strong metal to polymer assemblies is currently an important research subject thanks to its prominence to develop lightweight structures. Furthermore, laser welding is known to be a fast, reliable, and versatile joining process, and it was demonstrated recently that it can be applied to such metal to polymer systems. To enhance the mechanical properties of the laser-joined aluminum-polyamide (Al-PA) specimens, laser polishing and laser ablation processes have been implemented on the aluminum surface before joining. The polyamide surface was also treated with the laser beam, separately. The surfaces were tested by several characterization techniques before and after each surface treatment. Then aluminum and polyamide samples with different surface treatments have been joined with an identical laser joining process. The mechanical properties of the joints in single lap shear configuration are reported and the failure mechanisms are discussed based on micro-computed x-ray tomography imaging of joined specimens and microscopic analysis before failure. Results show that both surface treatments of aluminum significantly improve the shear load of the joint; however, with different failure mechanisms. Polyamide surface treatment and increasing degree of crystallinity are effective when combined with the laser polishing of the Al surface. This combination is responsible for further enhancement of the shear load of the joint to the limit of base metal strength which is approximately 60 % improvement compared to the untreated samples. Finally, energy dispersive X-ray mapping shows the physicochemical bonding between aluminum oxide and polyamide at the interface.