Recent developments and challenges of 3D-printed construction: a review of research fronts

In the last few years, scattered experiences of the application of additive manufacturing in the construction of buildings using 3D printing with robots or automated equipment have emerged around the world. These use a variety of procedures and suggest relevant advantages for the construction industry. In order to identify the different processes and features in development in this field and to guide future research and applications, this article presents a review of the literature on the main aspects involved in the use of 3D printing in the construction sector. The review includes state-of-the-art material mixtures, printing technologies, and potential uses, as well as a novel analysis of building strategies, management systems, and benefits stated about this new approach for construction. It reveals progressive experimentation regarding diverse features, with challenges related to the consolidation of procedures and this technology’s readiness to participate in the building market

Toolpath Planning Methodology for Multi-Gantry Fused Filament Fabrication 3D Printing

Additive manufacturing (AM) has revolutionized the way industries manufacture and prototype products. Fused filament fabrication (FFF) is one of the most popular processes in AM as it is inexpensive, requires low maintenance, and has high material utilization. However, the biggest drawback that prevents FFF printing from being widely implemented in large-scale production is the cycle time. The most practical approach is to allow multiple collaborating printheads to work simultaneously on different parts of the same object. However, little research has been introduced to support the aforementioned approach. Hence a new toolpath planning methodology is proposed in this paper. The objectives are to create a collision-free toolpath for each printhead while maintaining the mechanical performance of the printed model. The proposed method utilizes the Tabu Search heuristic and a combination of two subroutines: collision checking and collision resolution (TS-CCR). A computer simulation was used to compare the performance of the proposed method with the industry-standard approach in terms of cycle time. Physical experimentation is conducted to validate the mechanical strength of the TS-CCR specimens. The experiment also validated that the proposed toolpath can be executed on a custom multi-gantry setup without a collision. Experimental results indicated that the proposed TS-CCR can create toolpaths with shorter makespans than the current standard approach while achieving better ultimate tensile strength (UTS). This research represents opportunities for developing general toolpath planning for concurrent 3D printing

A bioinspired optimization strategy: to minimize the travel segment of the nozzle to accelerate the fused deposition modeling process

The fused deposition modeling process of digital printing uses a layer-by-layer approach to form a three-dimensional structure. Digital printing takes more time to fabricate a 3D model, and the speed varies depending on the type of 3D printer, material, geometric complexity, and process parameters. A shorter path for the extruder can speed up the printing process. However, the time taken for the extruder during printing (deposition) cannot be reduced, but the time taken for the extruder travel (idle move) can be reduced. In this study, the idle travel of the nozzle is optimized using a bioinspired technique called "ant colony optimization" (ACO) by reducing the travel transitions. The ACO algorithm determines the shortest path of the nozzle to reduce travel and generates the tool paths as G-codes. The proposed method’s G-code is implemented and compared with the G-code generated by the commercial slicer, Cura, in terms of build time. Experiments corroborate this finding: the G-code generated by the ACO algorithm accelerates the FDM process by reducing the travel movements of the nozzle, hence reducing the part build time (printing time) and increasing the strength of the printed object

A Comprehensive Survey on Particle Swarm Optimization Algorithm and Its Applications

Particle swarm optimization (PSO) is a heuristic global optimization method, proposed originally by Kennedy and Eberhart in 1995. It is now one of the most commonly used optimization techniques. This survey presented a comprehensive investigation of PSO. On one hand, we provided advances with PSO, including its modifications (including quantum-behaved PSO, bare-bones PSO, chaotic PSO, and fuzzy PSO), population topology (as fully connected, von Neumann, ring, star, random, etc.), hybridization (with genetic algorithm, simulated annealing, Tabu search, artificial immune system, ant colony algorithm, artificial bee colony, differential evolution, harmonic search, and biogeography-based optimization), extensions (to multiobjective, constrained, discrete, and binary optimization), theoretical analysis (parameter selection and tuning, and convergence analysis), and parallel implementation (in multicore, multiprocessor, GPU, and cloud computing forms). On the other hand, we offered a survey on applications of PSO to the following eight fields: electrical and electronic engineering, automation control systems, communication theory, operations research, mechanical engineering, fuel and energy, medicine, chemistry, and biology. It is hoped that this survey would be beneficial for the researchers studying PSO algorithms

Survey on Additive Manufacturing, Cloud 3D Printing and Services

Cloud Manufacturing (CM) is the concept of using manufacturing resources in a service oriented way over the Internet. Recent developments in Additive Manufacturing (AM) are making it possible to utilise resources ad-hoc as replacement for traditional manufacturing resources in case of spontaneous problems in the established manufacturing processes. In order to be of use in these scenarios the AM resources must adhere to a strict principle of transparency and service composition in adherence to the Cloud Computing (CC) paradigm. With this review we provide an overview over CM, AM and relevant domains as well as present the historical development of scientific research in these fields, starting from 2002. Part of this work is also a meta-review on the domain to further detail its development and structure

Multi-Objective UAV Mission Planning Using Evolutionary Computation

This investigation purports to develop a new model for multiple autonomous aircraft mission routing. Previous research both related and unrelated to this endeavor have used classic combinatoric problems as models for Unmanned Aerial Vehicle (UAV) routing and mission planning. This document presents the concept of the Swarm Routing Problem (SRP) as a new combinatorics problem for use in modeling UAV swarm routing, developed as a variant of the Vehicle Routing Problem with Time Windows (VRPTW). The SRP removes the single vehicle per target restraint and changes the customer satisfaction requirement to one of vehicle on location volume. The impact of these alterations changes the vehicle definitions within the problem model from discrete units to cooperative members within a swarm. This represents a more realistic model for multi-agent routing as a real world mission plan would require the use of all airborne assets across multiple targets, without constraining a single vehicle to a single target. Solutions to the SRP problem model result in route assignments per vehicle that successfully track to all targets, on time, within distance constraints. A complexity analysis and multi-objective formulation of the VRPTW indicates the necessity of a stochastic solution approach leading to the development of a multi-objective evolutionary algorithm. This algorithm design is implemented using C++ and an evolutionary algorithm library called Open Beagle. Benchmark problems applied to the VRPTW show the usefulness of this solution approach. A full problem definition of the SRP as well as a multi-objective formulation parallels that of the VRPTW method. Benchmark problems for the VRPTW are modified in order to create SRP benchmarks. These solutions show the SRP solution is comparable or better than the same VRPTW solutions, while also representing a more realistic UAV swarm routing solution

Swarm Robotics

Collectively working robot teams can solve a problem more efficiently than a single robot, while also providing robustness and flexibility to the group. Swarm robotics model is a key component of a cooperative algorithm that controls the behaviors and interactions of all individuals. The robots in the swarm should have some basic functions, such as sensing, communicating, and monitoring, and satisfy the following properties

Process Planning for Assembly and Hybrid Manufacturing in Smart Environments

Manufacturers strive for efficiently managing the consequences arising from the product proliferation during the entire product life cycle. New manufacturing trends such as smart manufacturing (Industry 4.0) present a substantial opportunity for managing variety. The main objective of this research is to help the manufacturers with handling the challenges arising from the product variety by utilizing the technological advances of the new manufacturing trends. This research focuses mainly on the process planning phase. This research aims at developing novel process planning methods for utilizing the technological advances accompanied by the new manufacturing trends such as smart manufacturing (Industry 4.0) in order to manage the product variety. The research has successfully addressed the macro process planning of a product family for two manufacturing domains: assembly and hybrid manufacturing. A new approach was introduced for assembly sequencing based on the notion of soft-wired galled networks used in evolutionary studies in Biological and phylogenetic sciences. A knowledge discovery model was presented by exploiting the assembly sequence data records of the legacy products in order to extract the embedded knowledge in such data and use it to speed up the assembly sequence planning. The new approach has the capability to overcome the critical limitation of assembly sequence retrieval methods that are not able to capture more than one assembly sequence for a given product. A novel genetic algorithm-based model was developed for that purpose. The extracted assembly sequence network is representing alternative assembly sequences. These alternative assembly sequences can be used by a smart system in which its components are connected together through a wireless sensor network to allow a smart material handling system to change its routing in case any disruptions happened. A novel concept in the field of product variety management by generating product family platforms and process plans for customization into different product variants utilizing additive and subtractive processes is introduced for the first time. A new mathematical programming optimization model is proposed. The model objective is to provide the optimum selection of features that can form a single product platform and the processes needed to customize this platform into different product variants that fall within the same product family, taking into consideration combining additive and subtractive manufacturing. For multi-platform and their associated process plans, a phylogenetic median-joining network algorithm based model is used that can be utilized in case of the demand and the costs are unknown. Furthermore, a novel genetic algorithm-based model is developed for generating multi-platform, and their associated process plans in case of the demand and the costs are known. The model\u27s objective is to minimize the total manufacturing cost. The developed models were applied on examples of real products for demonstration and validation. Moreover, comparisons with related existing methods were conducted to demonstrate the superiority of the developed models. The outcomes of this research provide efficient and easy to implement process planning for managing product variety benefiting from the advances in the technology of the new manufacturing trends. The developed models and methods present a package of variety management solutions that can significantly support manufacturers at the process planning stage

A Review on Remanufacturing Reverse Logistics Network Design and Model Optimization

Remanufacturing has gained great recognition in recent years due to its economic and environmental benefits and effectiveness in the value retention of waste products. Many studies on reverse logistics have considered remanufacturing as a key node for network optimization, but few literature reviews have explicitly mentioned remanufacturing as a main feature in their analysis. The aim of this review is to bridge this gap. In total, 125 papers on remanufacturing reverse logistics network design have been reviewed and conclusions have been drawn from four aspects: (1) in terms of network structure, the functional nodes of new hybrid facilities and the network structure combined with the remanufacturing technologies of products are the key points in the research. (2) In the mathematical model, the multi-objective function considered from different aspects, the uncertainty of recovery time and recovery channel in addition to quantity and quality, and the selection of appropriate algorithms are worth studying. (3) While considering product types, the research of a reverse logistics network of some products is urgently needed but inadequate, such as medical and furniture products. (4) As for cutting-edge technologies, the application of new technologies, such as intelligent remanufacturing technology and big data, will have a huge impact on the remanufacturing of a reverse logistics network and needs to be considered in our research

Recent Advances in the Development of Biomimetic Materials

: In this review, we focused on recent efforts in the design and development of materials with biomimetic properties. Innovative methods promise to emulate cell microenvironments and tissue functions, but many aspects regarding cellular communication, motility, and responsiveness remain to be explained. We photographed the state-of-the-art advancements in biomimetics, and discussed the complexity of a "bottom-up" artificial construction of living systems, with particular highlights on hydrogels, collagen-based composites, surface modifications, and three-dimensional (3D) bioprinting applications. Fast-paced 3D printing and artificial intelligence, nevertheless, collide with reality: How difficult can it be to build reproducible biomimetic materials at a real scale in line with the complexity of living systems? Nowadays, science is in urgent need of bioengineering technologies for the practical use of bioinspired and biomimetics for medicine and clinics