MILP models to minimise makespan in additive manufacturing machine scheduling problems

PurposeThis study aims to evaluate and compare the macroscopic properties of commercial acrylonitrile-butadiene-styrene (ABS) processed by two different types of additive manufacturing (AM) machines. The focus is also on the effect of multiple closed-loop recycling of ABS.Design/methodology/approachA conventional direct-drive, Cartesian-type machine and a Bowden, Delta-type machine with an infrared radiant heating system are used to manufacture test specimens molded in ABS. Afterward, multiple closed-loop recycling cycles are conducted, involving consecutive AM (four times) and recycling (three times). The rheological, mechanical, morphological and physicochemical properties are investigated.FindingsThe type of machine affects the quality of the produced parts. The machine containing an infrared radiant system in a temperature-controlled chamber produces parts showing higher mechanical properties and filling fraction, although it increases the yellowing. Closed-loop recycling of ABS for AM is applicable for at least two cycles, inducing a slight increase in tensile modulus (ca. 5%) and in tensile strength (ca. 13%) and a decrease in the impact strength (ca. 14%) and melt viscosity. An increase in the filling fraction of the AM parts promotes an increase in tensile strength and tensile modulus, although it does not influence the impact strength. Furthermore, multiple closed-loop recycling does not affect the overall chemical structure of ABS.Practical implicationsControlling the environmental temperature and using infrared radiant heating during AM of ABS improves the quality of the produced parts. Closed-loop recycling of ABS used in AM is feasible up to at least two recycling steps, supporting the implementation of a circular economy for polymer-based AM.Originality/valueThis study shows original results regarding the assessment of the effect of different types of AM machines on the main end-use properties of ABS parts and the influence of multiple closed-loop recycling on the characteristics of ABS fabricated by the most suited AM machine with an infrared radiant heating system and a temperature-controlled environment.

Additive manufacturing of biomedical implants: A feasibility assessment via supply-chain cost analysis

This paper addresses the problem of scheduling n jobs on a single machine and on m identical parallel machines to minimize the completion time variance of jobs. This problem of scheduling jobs on parallel machines is motivated by a case study in an automobile ancillary unit. First, a heuristic to solve the single-machine scheduling problem is proposed. The parallel-machine scheduling problem is solved in two phases: job-allocation phase and job-sequencing phase. Two heuristics are proposed in the job-allocation phase, whereas in the job-scheduling phase, the single-machine scheduling approach is used. In this paper, both versions of parallel-machine scheduling problem (restricted and unrestricted) are considered. A good upper bound is obtained using a genetic algorithm, to evaluate the performance of the proposed heuristics for the parallel-machine scheduling problem. An extensive computation evaluation of the proposed heuristics is presented for both single-machine scheduling problem and the parallel-machine scheduling problem (especially considering the case study), along with the comparison of performances with the existing heuristics in the literature.

In most industrial additive manufacturing (AM) applications a set of AM machines (AM-Fleet) are used in parallel. An AM-Fleet often consists of machines from various vendors and may include different AM processes. AM processes often suffer from poor repeatability within a single build, between builds on the same machine, and from machine to machine. AM's lack of robustness is often attributed to insufficient in-process monitoring and feedback control, as well as unknown modeling dynamics, and a lack of process standards. To effectively monitor and control AM-Fleets, system-level approaches must be devised. In this work, a centralized approach is proposed for the system-level control and management of AM-Fleets. Integrating such an approach has advantages in terms of system-level intelligent decision making for AM-Fleets. Key problems that needs to be solved and the challenges for a centralized approach are discussed in this work. The architecture of the proposed framework is presented with discussions on the individual components. A discrete event model for the system-level monitoring and control of AM machines is also proposed to support the presented framework. The use of discrete event models creates an abstract representation of the AM machine that enables the supervision of the physical system. An illustrative example that demonstrates a system-level run-to-run anomaly detection case is discussed. The proposed framework will provide an analytical foundation for systematic anomaly detection, scheduling, and decision making in AM-Fleets.

PurposeIn this era of Fourth Industrial Revolution, also known as Industry 4.0, additive manufacturing (AM) has been recognized as one of the nine technologies of Industry 4.0 that will revolutionize different sectors (such as manufacturing and industrial production). Therefore, this study aims to focus on “Additive Manufacturing Education” and the primary aim of this study is to investigate the impacts of AM technology at selected South African universities and develop a proposed framework for effective AM education using South African universities as the case study.Design/methodology/approachQuantitative research approach was used in this study, that is, a survey (questionnaire) was designed specifically to investigate the impacts of the existing AM technology/education and the facilities at the selected South African universities. The survey was distributed to several students (undergraduate and postgraduate) and the academic staffs within the selected universities. The questionnaire contained structured questions based on five factors/variables and followed by two open-ended questions. The data were collected and analyzed using statistical tools and were interpreted accordingly (i.e. both the closed and open-ended questions). The hypotheses were stated, tested and accepted. In conclusion, the framework for AM education at the universities was developed.FindingsBased on different literature reviewed on “framework for AM technology and education”, there is no specific framework that centers on AM education and this makes it difficult to find an existing framework for AM education to serve as a landscape to determine the new framework for AM education at the universities. Therefore, the results from this study made a significant contribution to the body of knowledge in AM, most especially in the area of education. The significant positive responses from the respondents have shown that the existing AM in-house facilities at the selected South African universities is promoting AM education and research activities. This study also shows that a number of students at the South African universities have access to AM/3D printing lab for design and research purposes. Furthermore, the findings show that the inclusion of AM education in the curriculum of both the science and engineering education is South Africa will bring very positive results. The introduction of a postgraduate degree in AM such as MSc or MEng in AM will greatly benefit the South African universities and different industries because it will increase the number of AM experts and professionals. Through literature review, this study was able to identify five factors (which includes sub-factors) that are suitable for the development of a framework for AM education, and this framework is expected to serve as base-line or building block for other universities globally to build/develop their AM journey.Research limitations/implicationsThe survey was distributed to 200 participants and 130 completed questionnaires were returned. The target audience for the survey was mainly university students (both undergraduate and postgraduate) and the academics who have access to AM machines or have used the AM/3D printing lab/facilities on their campuses for both academic and research purposes. Therefore, one of the limitations of the survey is the limited sample size; however, the sample size for this survey is considered suitable for this type of research and would allow generalization of the findings. Nevertheless, future research on this study should use larger sample size for purpose of results generalization. In addition, this study is limited to quantitative research methodology; future study should include qualitative research method. Irrespective of any existing or developed framework, there is always a need to further improve the existing framework, and therefore, the proposed framework for AM education in this study contained only five factors/variables and future should include some other factors (AM commercialization, AM continuous Improvement, etc.) to further enhance the framework.Practical implicationsThis study provides the readers and researchers within the STEM education, industry or engineering education/educators to see the importance of the inclusion of AM in the university curriculum for both undergraduate and postgraduate degrees. More so, this study serves as a roadmap for AM initiative at the universities and provides necessary factors to be considered when the universities are considering or embarking on AM education/research journey at their universities. It also serves as a guideline or platform for various investors or individual organization to see the need to invest in AM education.Originality/valueThe contribution of this study towards the existing body of knowledge in AM technology, specifically “AM education research” is in the form of proposed framework for AM education at the universities which would allow the government sectors/industry/department/bodies and key players in AM in South Africa and globally to see the need to invest significantly towards the advancement of AM technology, education and research activities at various universities.

Despite more than three decades since the beginning of Additive Manufacturing (AM), many challenges and issues prevent the industrialization of this technology. In fact, productivity is related to repetitive production of the same part under the same fabrication conditions. Currently, it is difficult to guarantee this repetitive production due to uncertainty issues, which represents the main obstacle of AM industrialization. In this paper, the uncertainty issues can be divided into two levels. The first level is related to the used AM machine itself which can be considered as robot of 3 degrees of freedom (x, y and z). In addition to its movement in three directions, this robot (AM machine) extrudes melted materials. The second level is related to the associated robots with 3D printing machines. In addition to summarizing some previous works and reviews, this mini review has the objective to provide new ideas to develop new strategies to overcome some uncertainty issues to contribute to the industrialization of AM technology. Furthermore, it paves the way to establish a concurrent AM / robotics loop in order to use AM for robotics and robotics for AM. The different developments should lead to elaborating Industrialization Standard for AM (IS4AM) where the different findings and recomm

The topographical, microstructural, and mechanical surface properties of additively manufactured components depend on variations of several processing parameters. Most studies focus on a narrow range of parameter variations, with the surface and subsurface characteristics being determined for that limited set of conditions. This makes it difficult to optimize these properties for additively manufactured parts and the energy consumption of the additive-manufacturing (AM) process. Our study looks at the systematic variation of two key AM parameters over their full range using a commercial AM machine. The laser scanning speed (500–1700 mm/s) and the laser power (250–370 W) were the parameters used. We analyze and discuss how these two parameters affect the surface topography, roughness, porosity, microstructure and hardness, as well as their anisotropy for the top and side surfaces during powder bed fusion, using a single AM machine and printing strategy. The aluminum alloy AlSi10Mg was selected for the study. It is one of the most commonly used materials in die casting and has the potential to take advantage of AM technology, since these parts can be lightweight, have good mechanical properties and to be produced with complex shapes.

Lack of industrially available materials for additive manufacturing (AM) of metallic materials along with the promises of materials with improved or unique properties provides a strong drive for developing new process/material combinations. As powder bed technologies for metallic materials are relatively new to the market, and to some extent are only maturing, developers of new process/material combinations have certain challenges to overcome. Firstly, basic knowledge on the behavior of materials (even those well established for other applications) under extreme conditions of melting/solidification with beam-based AM methods is far from being adequate. Secondly, manufacturing of the equipment is up to date driven by industrial application, thus optimization of the AM machines for small test batches of powders is still belongs to research and development projects. Also, majority of the powder manufacturers are primarily driven by the market development, and even they are well aware of the demands imposed by the powder bed AM machines, availability of small test batches of adequate powders may be problematic or at least quite costly for the R&D oriented users. Present paper describes the experiences in developing new materials for EBM A2 machine by Arcam EBM, modified for operating with powder batches of 100-200 ml and less. In particular it discusses achievements and challenges of working with powders from different materials with specifications far beyond the range suggested by machine manufacturer. Also it discusses the possibility of using blended rather than pre-alloyed powders for achieving both composite-like and alloyed materials in the same part by steering electron beam energy deposition strategy.

Additive manufacturing (AM) can enable complex and novel designs that are otherwise infeasible with traditional metal manufacturing techniques. In low-volume production scenarios, particularly for specialized applications which can benefit from customized designs, traditional metal manufacturing techniques may be limited by costs associated with tooling. The ability to produce novel designs is particularly interesting in heat exchanger (HX) design where performance is often largely based on the achievable geometry. However, consequences of the AM process such as surface roughness, deviation from specified dimensions, and defects such as cracks and voids could also affect HX performance. These effects may vary between identically designed AM parts based on AM machine settings. The goal of this work is to gain a better understanding of the performance variations across several different implementations of the same heat exchanger design. More specifically, the objective of this work is to experimentally compare the thermal and hydraulic performances of a traditionally manufactured, stamped-aluminum aircraft oil cooler and three geometrically equivalent, additively manufactured counterparts. Compared to the traditionally manufactured heat exchanger, the AM HXs exhibited significantly higher air-side pressure loss and higher heat transfer despite having nominally similar geometries. Between AM HXs, there were slight differences in surface roughness characteristics based on optimal profilometry measurements. In addition, the thickness of the air-side fins varied as much as 15 percent between the AM HXs. The net effect, without the contribution of each cause clear, was higher air-side pressure loss and slightly higher heat transfer for the AM HX with thicker fins. This study indicates that functional heat exchangers built using AM vary in performance even when the same digital model is used to print them, and that AM HXs as a group perform considerably differently than their traditional counterparts. Thus, there is a need to account for anticipated surface roughness, geometric deviations, and potential defects when designing HXs. Proper consideration could result in improved thermal performance for future heat exchangers.

Goal: This research identifies the optimal location for additive manufacturing (AM) facilities within the spare parts supply chain, addressing a critical yet underexplored dimension in the literature on strategic facility location for AM technology deployment.Design / Methodology / Approach: The study integrates agent-based discrete event simulation with scenario analysis to evaluate four facility locations for four distinct spare parts. The model aims to reduce order fulfillment losses and opportunity costs by supporting evidence-based location decisions.Results: The findings indicate that the Thane location is the most suitable for establishing an AM facility, offering a balanced trade-off between supply reliability and economic efficiency.Limitations of the investigation: The scope is confined to a specific case involving four locations and four spare parts, which may limit generalizability. The study’s scenario-based approach also relies on assumptions that warrant further validation.Practical implications: The results offer actionable insights for firms adopting AM in spare parts management. Strategic facility placement enhances service responsiveness, reduces downtime, and supports cost-effective ful-fillment strategies.Originality / Value: This research provides an incremental empirical contribution by proposing and demonstrat-ing a simulation-based AM facility location selection framework, supported by real-world case data. It addresses a less explored strategic decision of AM facility placement, considering dynamic operational uncertainties, thereby extending the existing literature on AM supply chain design.

Increasing the industrial uptake of additive manufacturing processes: A training framework

Scheduling identical parallel machines with tooling constraints

Biomonitoring of Metal Exposure During Additive Manufacturing (3DPrinting).

The growth of additive manufacturing as a disruptive technology poses nuclear proliferation concerns worthy of serious consideration. Additive manufacturing began in the early 1980s with technological advances in polymer manipulation, computer capabilities, and computer-aided design (CAD) modeling. It was originally limited to rapid prototyping; however, it eventually developed into a complete means of production that has slowly penetrated the consumer market. Today, additive manufacturing machines can produce complex and unique items in a vast array of materials including plastics, metals, and ceramics. These capabilities have democratized the manufacturing industry, allowing almost anyone to produce items as simple as cup holders or as complex as jet fuel nozzles. Additive manufacturing, or three-dimensional (3D) printing as it is commonly called, relies on CAD files created or shared by individuals with additive manufacturing machines to produce a 3D object from a digital model. This sharing of files means that a 3D object can be scanned or rendered as a CAD model in one country, and then downloaded and printed in another country, allowing items to be shared globally without physically crossing borders. The sharing of CAD files online has been a challenging task for the export controls regime to manage over the years, and additive manufacturing could make these transfers more common. In this sense, additive manufacturing is a disruptive technology not only within the manufacturing industry but also within the nuclear nonproliferation world. This paper provides an overview of additive manufacturing concerns of proliferation.

Test artefacts for additive manufacturing: A design methodology review