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Metal laser-powder-bed-fusion using laser-beam parts are particularly susceptible to contamination due to particles attached to the surface. This may compromise so-called technical cleanliness (e.g. in NASA RPTSTD-8070, ASTM G93, ISO 14952 or ISO 16232), which is important for many 3D-printed components, such as implants or liquid rocket engines. The purpose of the presented comparative study is to show how cleanliness is improved by design and different surface treatment methods.

Convex and concave test parts were designed, built and surface-treated by combinations of media blasting, electroless nickel plating and electrochemical polishing. After cleaning and analysing the technical cleanliness according to ASTM and ISO standards, effects on particle contamination, appearance, mass and dimensional accuracy are presented.

Contamination reduction factors are introduced for different particle sizes and surface treatment methods. Surface treatments were more effective for concave design features, however, the initial and resulting absolute particle contamination was higher. Results further indicate that there are trade-offs between cleanliness and other objectives in design. Design guidelines are introduced to solve conflicts in design when requirements for cleanliness exist.

This paper recommends designing parts and corresponding process chains for manufacturing simultaneously. Incorporating post-processing characteristics into the design phase is both feasible and essential. In the experimental study, electroless nickel plating in combination with prior glass bead blasting resulted in the lowest total remaining particle contamination. This process applied for cleanliness is a novelty, as well as a comparison between the different surface treatment methods.

Fused Filament Fabrication (FFF) is one of the growing technologies in additive manufacturing, that can be used in a number of applications. In this method, process parameters can be customized and their simultaneous variation has conflicting impacts on various properties of printed parts such as dimensional accuracy (DA) and surface finish. These properties could be improved by optimizing the values of these parameters.

In this paper, four process parameters, namely, print speed, build orientation, raster width, and layer height which are referred to as “input variables” were investigated. The conflicting influence of their simultaneous variations on the DA of printed parts was investigated and predicated. To achieve this goal, a hybrid Genetic Algorithm – Artificial Neural Network (GA-ANN) model, was developed in C#.net, and three geometries, namely, U-shape, cube and cylinder were selected. To investigate the DA of printed parts, samples were printed with a central through hole. Design of Experiments (DoE), specifically the Rotational Central Composite Design method was adopted to establish the number of parts to be printed (30 for each selected geometry) and also the value of each input process parameter. The dimensions of printed parts were accurately measured by a shadowgraph and were used as an input data set for the training phase of the developed ANN to predict the behavior of process parameters. Then the predicted values were used as input to the Desirability Function tool which resulted in a mathematical model that optimizes the input process variables for selected geometries. The mean square error of 0.0528 was achieved, which is indicative of the accuracy of the developed model.

The results showed that print speed is the most dominant input variable compared to others, and by increasing its value, considerable variations resulted in DA. The inaccuracy increased, especially with parts of circular cross section. In addition, if there is no need to print parts in vertical position, the build orientation should be set at 0° to achieve the highest DA. Finally, optimized values of raster width and layer height improved the DA especially when the print speed was set at a high value.

By using ANN, it is possible to investigate the impact of simultaneous variations of FFF machines’ input process parameters on the DA of printed parts. By their optimization, parts of highly accurate dimensions could be printed. These findings will be of significant value to those industries that need to produce parts of high DA on FFF machines.

Design Science (DS) is a relatively new paradigm for addressing complex real-world problems through the design and evaluation of artifacts. Its constituent methodologies are currently being discussed and established in numerous related research fields, such as information systems and management (Hevner et al., 2004). However, a DS methodology that describes the “how to” is largely lacking, not only in the field of OM but in general. The Theory of Constraints (TOC) and its underlying thinking processes (TP) have produced several novel artifacts for addressing ill-structured real-world operations problems (Dettmer, 1997; Goldratt, 1994), but they have not been analyzed from a DS research standpoint. The purpose of this research is to demonstrate how TOC’s thinking process methodology can be used for conducting exploratory DS research in Operations and Supply Chain Management (OSCM).

A case study of spare parts replenishment illustrates the use of TOC’s thinking processes in DS to structure an initially unstructured problem context and to facilitate the design of a novel solution.

TOC’s thinking processes are an effective methodology for problem-solving DS research, enabling the development of novel solutions in initially unstructured and wicked problem situations. Combined with structured CIMO design logic TOC’s thinking process offers a systematic method for exploring wicked problems, designing novel solutions, and demonstrating theoretical contributions.

The implication for research is that TOC’s thinking process methodology can provide important elements of the lacking “how to” methodology for DS research, not only for the field of OM but in general for the field of management.

The practical outcome of the research is a novel design for dynamic buffer-based replenishment that extends beyond organizational boundaries.

This work shows how the thinking processes can be used in DS research to develop rigorous design propositions for ill-structured problems.

The article addresses the optimization of safety stock service levels for parts in a repair kit. The work was undertaken to assist a public transit entity that stores thousands of parts used to repair equipment acquired over many decades. Demand is intermittent, procurement lead times are long, and the total inventory investment is significant.

Demand exists for repair kits, and a repair cannot start until all required parts are available. The cost model includes holding cost to carry the part being modeled as well as shortage cost that consists of the holding cost to carry all other repair kit parts for the duration of the part’s lead time. The model combines deterministic and stochastic approaches by assuming a fixed ordering cycle with Poisson demand.

The results show that optimal service levels vary as a function of repair demand rate, part lead time, and cost of the part as a percentage of the total part cost for the repair kit. Optimal service levels are higher for inexpensive parts and lower for expensive parts, although the precise levels are impacted by repair demand and part lead time.

The proposed model can impact society by improving the operational performance and efficiency of public transit systems, by ensuring that home repair technicians will be prepared for repair tasks, and by reducing the environmental impact of electronic waste consistent with the right-to-repair movement.

The optimization model is unique because (1) it quantifies shortage cost as the cost of unnecessary holding other parts in the repair kit during the shortage time, and (2) it determines a unique service level for each part in a repair kit bases on its lead time, its unit cost, and the total cost of all parts in the repair kit. Results will be counter-intuitive for many inventory managers who would assume that more critical parts should have higher service levels.

To redesign the spare parts (MRO) inventory management at Company XYZ's warehouse, considering the conditions after the COVID-19 pandemic.

To address this research project, the authors integrated three methodologies: action research, Lean Six Sigma (DMAIC) and Cross Industry Standard Process for Data Mining. These methodologies integrated the Lean Six Sigma (LSS) 4.0 framework applied in this project.

The spare parts inventory value was reduced by 15%, and inventory turnover increased by 120% without negatively impacting the internal service level.

Practitioners leading or participating in continuous improvement projects (CIPs) should consider data quality (data available and data trustworthiness), problem-solving approach and target area involvement to achieve CIP goals. Otherwise, the LSS 4.0 could fail or extend its duration by several weeks or months.

This project shows the importance of controlling a target area before deciding to conduct a LSS 4.0 project. To address this problem, the LSS 4.0 team implemented 5S during the measure phase of the DMAIC. Also, this project offers significant practitioner and theoretical contributions to the body of knowledge about LSS 4.0.

Material extrusion (ME) is a low-cost additive manufacturing (AM) technique that is capable of producing metallic components using desktop 3D printers through a three-step printing, debinding and sintering process to obtain fully dense metallic parts. However, research on ME AM, specifically fused filament fabrication (FFF) of 316L SS, has mainly focused on improving densification and mechanical properties during the post-printing stage; sintering parameters. Therefore, this study aims to investigate the effect of varying processing parameters during the initial printing stage, specifically nozzle temperatures, T_n (190°C–300°C) on the relative density, porosity, microstructures and microhardness of FFF 3D printed 316L SS.

Cube samples (25 x 25 x 25 mm) are printed via a low-cost Artillery Sidewinder X1 3D printer using a 316L SS filament comprising of metal-polymer binder mix by varying nozzle temperatures from 190 to 300°C. All samples are subjected to thermal debinding and sintering processes. The relative density of the sintered parts is determined based on the Archimedes Principle. Microscopy and analytical methods are conducted to evaluate the microstructures and phase compositions. Vickers microhardness (HV) measurements are used to assess the mechanical property. Finally, the correlation between relative density, microstructures and hardness is also reported.

The results from this study suggest a suitable temperature range of 195°C–205°C for the successful printing of 316L SS green parts with high dimensional accuracy. On the other hand, T_n = 200°C yields the highest relative density (97.6%) and highest hardness (292HV) in the sintered part, owing to the lowest porosity content (<3%) and the combination of the finest average grain size (∼47 µm) and the presence of Cr23C6 precipitates. However, increasing T_n = 205°C results in increased porosity percentage and grain coarsening, thereby reducing the HV values. Overall, these outcomes suggest that the microstructures and properties of sintered 316L SS parts fabricated by FFF AM could be significantly influenced even by adjusting the processing parameters during the initial printing stage only.

This paper addresses the gap by investigating the impact of initial FFF 3D printing parameters, particularly nozzle temperature, on the microstructures and physical characteristics of sintered FFF 316L SS parts. This study provides an understanding of the correlation between nozzle temperature and various factors such as dimensional integrity, densification level, microstructure and hardness of the fabricated parts.

Fused deposition modeling (FDM) nowadays offers promising future applications for fabricating not only thermoplastic-based polymers but also composite PLA/Metal alloy materials, this capability bridges the need for metallic components in complex manufacturing processes. The research is to explore the manufacturability of multi-metal parts by printing green bodies of PLA/multi-metal objects, carrying these objects to the debinding process and varying the sintering parameters.

Three different sample types of SS316L part, Inconel 718 part and bimetallic composite of SS316L/IN718 were effectively printed. After the debinding process, the printed parts (green bodies), were isothermally sintered in non-vacuum chamber to investigate the fusion behavior at four different temperatures in the range of 1270 °C−1530 °C for 12 h and slowly cooled in the furnace. All samples was assessed including geometrical assessment to measure the shrinkage, characterization (XRD) to identify the crystallinity of the compound and microstructural evolution (Optical microscopy and SEM) to explore the porosity and morphology on the surface. The hardness of each sample types was measured and compared. The sintering parameter was optimized according to the microstructural evaluation on the interface of SS316L/IN718 composite.

The investigation indicated that the de-binding of all the samples was effectively succeeded through less weight until 16% when the PLA of green bodies was successfully evaporated. The morphology result shows evidence of an effective sintering process to have the grain boundaries in all samples, while multi-metal parts clearly displayed the interface. Furthermore, the result of XRD shows the tendency of lower crystallinity in SS316L parts, whilst IN718 has a high crystallinity. The optimal sintering temperature for SS316L/IN718 parts is 1500 °C. The hardness test concludes that the higher sintering temperature gives a higher hardness result.

This study highlights the successful sintering of a bimetallic stainless steel 316 L/Inconel 718 composite, fabricated via dual-nozzle fused deposition modeling, in a non-vacuum environment at 1500 °C. The resulting material displayed maximum hardness values of 872 HV for SS316L and 755.5 HV for IN718, with both materials exhibiting excellent fusion without any cracks.

This paper aims to determine the type of supplier involvement in terms of time and extent of supplier involvement in automobile product development based on the characteristics of parts in the Iranian automotive industry.

The paper proposes the clustering and analytic hierarchy process (AHP) methods. Combining the K-means clustering method and metaheuristic algorithms, the genetic algorithm (GA) and particle swarm optimization (PSO) algorithm are applied to achieve better clustering results.

The results show that lack of internal knowledge, high technology change and complexity of parts increase the need to outsource the design process. In addition to these reasons, high development costs and high interface complexity justify suppliers’ early involvement.

Most research only presents a conceptual framework for understanding the various levels of supplier involvement in new product development (NPD). However, in the automotive industry, numerous parts have differing degrees of importance and priority, and experts may have varying opinions based on different criteria. Therefore, the existing conceptual model for analyzing the types of involvement of each supplier is not practical. We have formulated a problem-solving approach that utilizes the clustering and AHP methods to analyze data obtained from qualitative research and determine the type of supplier involvement.

This paper aims to present the fabrication of 6061 aluminum alloy (AA6061) using a promising laser additive manufacturing process, called the laser-foil-printing (LFP) process. The process window of AA6061 in LFP was established to optimize process parameters for the fabrication of high strength, dense and crack-free parts even though AA6061 is challenging for laser additive manufacturing processes due to hot-cracking issues.

The multilayers AA6061 parts were fabricated by LFP to characterize for cracks and porosity. Mechanical properties of the LFP-fabricated AA6061 parts were tested using Vicker’s microhardness and tensile testes. The electron backscattered diffraction (EBSD) technique was used to reveal the grain structure and preferred orientation of AA6061 parts.

The crack-free AA6061 parts with a high relative density of 99.8% were successfully fabricated using the optimal process parameters in LFP. The LFP-fabricated parts exhibited exceptional tensile strength and comparable ductility compared to AA6061 samples fabricated by conventional laser powder bed fusion (LPBF) processes. The EBSD result shows the formation of cracks was correlated with the cooling rate of the melt pool as cracks tended to develop within finer grain structures, which were formed in a shorter solidification time and higher cooling rate.

This study presents the pioneering achievement of fabricating crack-free AA6061 parts using LFP without the necessity of preheating the substrate or mixing nanoparticles into the melt pool during the laser melting. The study includes a comprehensive examination of both the mechanical properties and grain structures, with comparisons made to parts produced through the traditional LPBF method.

This paper aims to identify the success factors (SFs) for total quality management (TQM) implementation in automotive spare parts companies to improve their business performance. It also intends to rank these factors in a hierarchical structure in descending order of their criticality.

In this study, a significant number of automotive spare parts companies were extensively surveyed to ascertain the contributions made by various factors toward the successful deployment of TQM practices. The collective and individual evaluation and ranking of the SFs were determined using the analytical hierarchy process (AHP) approach to develop the framework based on the prioritisation of the identified SFs.

The findings of the study show that five success factors, namely, internal environment, top management involvement, process management, supplier management and external environment, were ranked as critical factors with a total weight of 49.2%. Nine success factors, namely, employee training, teamwork, customer satisfaction, continuous improvement, communications, using new technologies, zero-defect processes, employee empowerment and benchmarking, were ranked as important with a total weight of 39.1%. The last five success factors, namely, strategic planning, quality policy, employee satisfaction, self-assessment and cost of quality, were ranked as minor factors with a total weight of 11.7%.

The current study adds to the existing body of knowledge for scholars and practitioners of TQM by specifically focusing on identifying and categorising the critical SFs for TQM implementation. The 19 categorised critical SFs have been used to construct a framework for TQM implementation in the Palestinian automotive spare parts companies. Such a framework would offer a comprehensive overview of the SFs, their categories, significance and priorities within a TQM environment in the automotive spare parts companies.