Rethinking reverse logistics: role of additive manufacturing technology in metal remanufacturing

2019 ◽  
Vol 31 (1) ◽  
pp. 124-144 ◽  
Author(s):  
Danielle Strong ◽  
Michael Kay ◽  
Thomas Wakefield ◽  
Issariya Sirichakwal ◽  
Brett Conner ◽  
...  
Keyword(s):  
Supply Chain ◽  
Additive Manufacturing ◽  
Facility Location ◽  
Reverse Logistics ◽  
Small And Medium Enterprises ◽  
Real Data ◽  
Cnc Machining ◽  
Numerical Control ◽  
Content Type ◽  
The Usa

Purpose Although the adoption of metal additive manufacturing (AM) for production has continuously grown, in-house access to production grade metal AM systems for small and medium enterprises (SMEs) is a major challenge due to costs of acquiring metal AM systems, specifically powder bed fusion AM. On the other hand, AM technology in directed energy deposition (DED) has been evolving in both: processing capabilities and adaptable configuration for integration within existing traditional machines that are available in most SME manufacturing facilities, e.g. computer numerical control (CNC) machining centers. Integrating DED with conventional processes such as machining and grinding into Hybrid AM is well suited for remanufacturing of metal parts. The paper aims to discuss these issues. Design/methodology/approach Classical facility location models are employed to understand the effects of SMEs adopting DED systems to offer remanufacturing services. This study identifies strategically located counties in the USA to advance hybrid AM for reverse logistics using North American Industry Classification System (NAICS) data on geographical data, demand, fixed and transportation costs. A case study is also implemented to explore its implications on remanufacturing of high-value parts on the reverse logistics supply chain using an aerospace part and NAICS data on aircraft maintenance, repair and overhaul facilities. Findings The results identify the candidate counties, their allocations, allocated demand and total costs. Offering AM remanufacturing services to traditional manufacturers decreases costs for SMEs in the supply chain by minimizing expensive new part replacement. The hubs also benefit from hybrid AM to repair their own parts and tools. Originality/value This research provides a unique analysis on reverse logistics through hybrid AM focused on remanufacturing rather than manufacturing. Facility location using real data is used to obtain results and offers insights into integrating AM for often overlooked aspect of remanufacturing. The study shows that SMEs can participate in the evolving AM economy through remanufacturing services using significantly lower investment costs.

Foam additive manufacturing technology: main characteristics and experiments for hull mold manufacturing

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Elodie Paquet ◽  
Alain Bernard ◽  
Benoit Furet ◽  
Sébastien Garnier ◽  
Sébastien Le Loch
Keyword(s):  
Additive Manufacturing ◽  
3D Printing ◽  
Manufacturing Process ◽  
Manufacturing Industry ◽  
Pressure Head ◽  
Manufacturing Technology ◽  
Cnc Machining ◽  
Numerical Control ◽  
Content Type ◽  
Additive Manufacturing Technology

Purpose The purpose of this paper is to present a novel methodology to produce a large boat hull with a foam additive manufacturing (FAM) process. To respond to shipping market needs, this new process is being developed. FAM technology is a conventional three-dimensional (3D) printing process whereby layers are deposited onto a high-pressure head mounted on a six-axis robotic arm. Traditionally, molds and masters are made with computer numerical control (CNC) machining or finished by hand. Handcrafting the molds is obviously time-consuming and labor-intensive, but even CNC machining can be challenging for parts with complex geometries and tight deadlines. Design/methodology/approach The proposed FAM technology focuses on the masters and molds, that are directly produced by 3D printing. This paper describes an additive manufacturing technology through which the operator can create a large part and its tools using the capacities of this new FAM technology. Findings The study shows a comparison carried out between the traditional manufacturing process and the additive manufacturing process, which is illustrated through an industrial case of application in the manufacturing industry. This work details the application of FAM technology to fabricate a 2.5 m boat hull mold and the results show the time and cost savings of FAM in the fabrication of large molds. Originality/value Finally, the advantages and drawbacks of the FAM technology are then discussed and novel features such as monitoring system and control to improve the accuracy of partly printed are highlighted.

Adaptive neuro-fuzzy fusion of multi-sensor data for monitoring of CNC machining

Sensor Review ◽  
2017 ◽  
Vol 37 (1) ◽  
pp. 78-81 ◽  
Author(s):  
Srdjan Jovic ◽  
Obrad Anicic ◽  
Milivoje Jovanovic
Keyword(s):  
Selection Process ◽  
Spindle Speed ◽  
Cnc Machining ◽  
Numerical Control ◽  
Periodic Component ◽  
Sensor Data ◽  
Depth Of Cut ◽  
Inference System ◽  
Content Type ◽  
Neuro Fuzzy

Purpose Acoustic emission (AE) could be used for prevention and detection of tool errors in Computer Numerical Control (CNC) machining. The purpose of this study is to analyze the AE form of CNC machining operations. Design/methodology/approach Experimental measurements were performed with three sensors on the CNC lathe to collect the data of the CNC machining. Adaptive neuro-fuzzy inference system (ANFIS) was applied for the fusion from the sensors’ signals to determine the strength of the signal periodic component among the sensors. Findings There were three inputs, namely, spindle speed, feed rate and depth of cut. ANFIS was also used to determine the inputs’ influence on the prediction of strength of the signal periodic component. Variable selection process was used to select the most dominant factors which affect the prediction of strength of the signal periodic component. Originality/value Results were shown that the spindle speed has the most dominant effect on the strength of the signal periodic component.

Optimal space filling for additive manufacturing

2016 ◽  
Vol 22 (4) ◽  
pp. 660-675 ◽  
Author(s):  
Sajan Kapil ◽  
Prathamesh Joshi ◽  
Hari Vithasth Yagani ◽  
Dhirendra Rana ◽  
Pravin Milind Kulkarni ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Manufacturing Process ◽  
Layered Manufacturing ◽  
Closed Curve ◽  
Numerical Control ◽  
Surface Finishing ◽  
Content Type ◽  
Single Pass ◽  
Connected Area ◽  
Area Filling

Purpose In additive manufacturing (AM) process, the physical properties of the products made by fractal toolpaths are better as compared to those made by conventional toolpaths. Also, it is desirable to minimize the number of tool retractions. The purpose of this study is to describe three different methods to generate fractal-based computer numerical control (CNC) toolpath for area filling of a closed curve with minimum or zero tool retractions. Design/methodology/approach This work describes three different methods to generate fractal-based CNC toolpath for area filling of a closed curve with minimum or zero tool retractions. In the first method, a large fractal square is placed over the outer boundary and then rest of the unwanted curve is trimmed out. To reduce the number of retractions, ends of the trimmed toolpath are connected in such a way that overlapping within the existing toolpath is avoided. In the second method, the trimming of the fractal is similar to the first method but the ends of trimmed toolpath are connected such that the overlapping is found at the boundaries only. The toolpath in the third method is a combination of fractal and zigzag curves. This toolpath is capable of filling a given connected area in a single pass without any tool retraction and toolpath overlap within a tolerance value equal to stepover of the toolpath. Findings The generated toolpath has several applications in AM and constant Z-height surface finishing. Experiments have been performed to verify the toolpath by depositing material by hybrid layered manufacturing process. Research limitations/implications Third toolpath method is suitable for the hybrid layered manufacturing process only because the toolpath overlapping tolerance may not be enough for other AM processes. Originality/value Development of a CNC toolpath for AM specifically hybrid layered manufacturing which can completely fill any arbitrary connected area in single pass while maintaining a constant stepover.

Effects of cloud computing assimilation on supply chain financing risks of SMEs

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Qiang Lu ◽  
Jinliang Chen ◽  
Hua Song ◽  
Xiangyu Zhou
Keyword(s):  
Cloud Computing ◽  
Supply Chain ◽  
Small And Medium Enterprises ◽  
Supply Chain Integration ◽  
Content Type ◽  
Supply Chain Financing ◽  
Medium Enterprises ◽  
The Relationship ◽  
Moderating Role

Purpose The purpose of this study is to examine how cloud computing assimilation reduces supply chain financing (SCF) risks of small and medium enterprises (SMEs). This study also investigated the mediating roles of internal and external supply chain integration between cloud computing assimilation and the SCF risks of SMEs, as well as the moderating role of environmental competitiveness. Design/methodology/approach Data was collected from surveys of SMEs located in China. Multiple regression analysis was used to validate the proposed theoretical model and research hypotheses. Findings The findings show that cloud computing assimilation could reduce the SCF risks of SMEs directly. The results also indicate that both internal and external supply chain integration mediate the relationship between cloud computing assimilation and SCF risks. Furthermore, environmental competitiveness inhibits the effects of cloud computing assimilation on SCF risks. Originality/value To our best knowledge, this is the preliminary study to explore the role of cloud computing assimilation in reducing the SCF risks of SMEs. Also, this study attempted to investigate the process by which cloud computing assimilation affects the SCF risks of SMEs.

Big data-driven supply chain and performance: a resource-based view

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Shampy Kamboj ◽  
Shruti Rana
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Small And Medium Enterprises ◽  
Data Driven ◽  
Equation Modeling ◽  
Firm Age ◽  
Content Type ◽  
Sustainable Performance ◽  
Medium Enterprises

PurposeThe main objective of this paper is to study the role of supply chain performance (SCP) as a mediator between big data-driven supply chain (BDDSC) and firm sustainable performance. In addition, the role of firm age as a moderator between BDDSC and SCP as well as between SCP and firm sustainable performance has also been explored.Design/methodology/approachThe 200 managers of medium or senior level positions in micro, small and medium enterprises (MSMEs) located at Delhi-NCR have been contacted. Further, collected data have been confirmed with confirmatory factor analysis (CFA). In this paper, structure equation modeling (SEM) has been employed to empirically check the proposed hypotheses and their relationships.FindingsThe findings confirmed that SCP mediates the link between BDDSC and firm sustainable performance. Additionally, firm age moderates the association between BDDSC and SCP as well as between SCP and firm sustainable performance.Research limitations/implicationsThe role of SCP and firm age between BDDSC and sustainable performance have been examined in the context of MSMEs in Delhi-NCR and thereby limit the generalization of results to other industries and country contexts.Originality/valueThe present study adds to the existing literature via recognizing the blackbox using SCP and firm age to comprehend BDDSC and firm sustainable performance relationship.

Episodic supply chains at times of disruption

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Christina Öberg
Keyword(s):  
Supply Chain ◽  
Additive Manufacturing ◽  
Supply Chains ◽  
Design Methodology ◽  
Secondary Data ◽  
Transformational Change ◽  
Content Type ◽  
Metal Additive Manufacturing ◽  
Contemporary Technology ◽  
Metal Additive

Purpose Additive manufacturing has been described as converting supply chains into demand chains. By focusing on metal additive manufacturing as a contemporary technology causing ongoing disruption to the supply chain, the purpose of this paper is to describe and discuss how incumbent firms act during an ongoing, transformational disruption of their supply chain. Design/methodology/approach Interviews and secondary data, along with seminars attracting approximately 600 individuals operating in metal additive manufacturing, form the empirical basis for this paper. Findings The findings of this paper indicate how disruption occurs at multiple positions in the supply chain. Episodic positions as conceptualised in this paper refer to how parties challenged by disruption attempt to reach normality while speeding the transformational disruption. Originality/value This paper contributes to previous research by theorising about episodic positions in light of a supply chain disruption. The empirical data are unique in how they capture supply chain change at the time of disruption and illustrate disruptive, transformational change to supply chains. The paper interlinks research on disruption from the innovation and supply chain literature, with contributions to both.

Modeling and analysis of the on-demand spare parts supply using additive manufacturing

2019 ◽  
Vol 25 (3) ◽  
pp. 473-487 ◽  
Author(s):  
Yuan Zhang ◽  
Stefan Jedeck ◽  
Li Yang ◽  
Lihui Bai
Keyword(s):  
Supply Chain ◽  
Additive Manufacturing ◽  
Spare Parts ◽  
Production Optimization ◽  
Arrival Process ◽  
Powder Bed Fusion ◽  
Content Type ◽  
Modeling And Analysis ◽  
Powder Bed ◽  
On Demand

PurposeDespite the widespread expectation that additive manufacturing (AM) will become a disruptive technology to transform the spare parts supply chain, very limited research has been devoted to the quantitative modeling and analysis on how AM could fulfill the on-demand spare parts supply. On the other hand, the choice of using AM as a spare parts supply strategy over traditional inventory is a rising decision faced by manufacturers and requires quantitative analysis for their AM-or-stock decisions. The purpose of this paper is to develop a quantitative performance model for a generic powder bed fusion AM system in a spare parts supply chain, thus providing insights into this less-explored area in the literature.Design/methodology/approachIn this study, analysis based on a discrete event simulation was carried out for the use of AM in replacement of traditional warehouse inventory for an on-demand spare parts supply system. Generic powder bed fusion AM system was used in the model, and the same modeling approach could be applied to other types of AM processes. Using this model, the impact of both spare parts demand characteristics (e.g. part size attributes, demand rates) and the AM operations characteristics (e.g. machine size and postpone strategy) on the performance of using AM to supply spare parts was studied.FindingsThe simulation results show that in many cases the AM operation is not as cost competitive compared to the traditional warehouse-based spare parts supply operation, and that the spare parts size characteristics could significantly affect the overall performance of the AM operations. For some scenarios of the arrival process of spare parts demand, the use of the batched AM production could potentially result in significant delay in parts delivery, which necessitates further investigations of production optimization strategies.Originality/valueThe findings demonstrate that the proposed simulation tool can not only provide insights on the performance characteristics of using AM in the spare parts supply chain, especially in comparison to the traditional warehousing system, but also can be used toward decision making for both the AM manufacturers and the spare parts service providers.

scholarly journals Additive manufacturing in the spare parts supply chain: hub configuration and technology maturity

2018 ◽  
Vol 24 (7) ◽  
pp. 1178-1192 ◽  
Author(s):  
Siavash H. Khajavi ◽  
Jan Holmström ◽  
Jouni Partanen
Keyword(s):  
Supply Chain ◽  
Additive Manufacturing ◽  
Spare Parts ◽  
Content Type ◽  
Local Manufacturing ◽  
Efficiency And Effectiveness ◽  
Industrial Operations ◽  
Production Configuration ◽  
Part Production

PurposeInnovative startups have begun a trend using laser sintering (LS) technology patents expiration, namely, by introducing LS additive manufacturing (AM) machines that can overcome utilization barriers, such as the costliness of machines and productivity limitation. The recent rise of this trend has led the authors to investigate this new class of machines in novel settings, including hub configuration. There are various supply chain configurations to supply spare parts in industrial operations. This paper aims to explore the promise of a production configuration that combines the benefits of centralized production with the flexibility of local manufacturing without the huge costs related to it.Design/methodology/approachThis study quantitatively examines the feasibility of different AM-enabled spare parts supply chain configurations. Using cost data extracted from a case study, three scenarios per AM machine technology are modeled and compared.FindingsResults suggest that hub production configuration depending on the utilized AM machines can provide economic efficiency and effectiveness to reduce equipment downtime. While previous studies have suggested the need for AM machines with efficiency for single part production for a distributed supply chain, the findings in this research illustrate the positive relationship between multi-part production capability and the feasibility of a hub manufacturing configuration establishment.Originality/valueThis study explores the promise of a production configuration that combines the benefits of centralized production with the flexibility of local manufacturing without the huge costs related to it. Although the existing body of knowledge contains research on production decentralization, research on various levels of decentralization is lacking. Using a real-world case study, this study aims to compare the feasibility of different levels of decentralization for AM-enabled spare parts supply chains.

Pollution optimisation study of logistics in SMEs

2019 ◽  
Vol 30 (4) ◽  
pp. 731-750 ◽  
Author(s):  
Anand Jaiswal ◽  
Cherian Samuel ◽  
G. Abhishek Ganesh
Keyword(s):  
Supply Chain ◽  
Small And Medium Enterprises ◽  
Pollutant Emission ◽  
Vehicular Pollution ◽  
Data Set ◽  
Content Type ◽  
Logistics Network ◽  
Pollution Emission ◽  
Optimisation Model ◽  
Medium Enterprises

Purpose The purpose of this paper is to provide a solution for greening the supply chain of small and medium enterprises (SMEs) by minimising the vehicular pollutant emission in the logistics network. Design/methodology/approach The paper proposes an optimisation model to reduce the pollution emission in the logistics of supply chain network in SMEs. The work considers vehicle routing and selection of suppliers, manufacturers and assemblers according to the availability of various Bharat Stage Emission Standards type vehicles. Introsort sorting based selection algorithm is used to solve the problem. The proposed solution is implemented using C++ on an experimental data set for analysing the model. Findings The outcome of the study is a pollution optimisation model for logistics of SMEs. The finding shows an approach to reduce total vehicular pollution emission in the logistics network in meeting the demand. The model is tested over an experimental study, and the result findings show which supply chain entities, type of environmental standard vehicles and vehicle routes are selected for the specific demand. Research limitations/implications The proposed model is confined to pollution optimisation with limited parameters only and does not consider cost and other factors that can be included in future work. Practical implications The work can be used for limiting pollution in logistics system as the corporate social responsibility of enterprises. Originality/value Proposed work presents a sustainable and green solution for pollution control in logistics activities of the SMEs.

scholarly journals Performance tradeoffs for spare parts supply chains with additive manufacturing capability servicing intermittent demand

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kyle C. McDermott ◽  
Ryan D. Winz ◽  
Thom J. Hodgson ◽  
Michael G. Kay ◽  
Russell E. King ◽  
...  
Keyword(s):  
Supply Chain ◽  
Additive Manufacturing ◽  
Production Capacity ◽  
Spare Part ◽  
Spare Parts ◽  
Mixed Integer ◽  
Network Configuration ◽  
Intermittent Demand ◽  
Content Type ◽  
Demand Patterns

PurposeThe study aims to investigate the impact of additive manufacturing (AM) on the performance of a spare parts supply chain with a particular focus on underlying spare part demand patterns.Design/methodology/approachThis work evaluates various AM-enabled supply chain configurations through Monte Carlo simulation. Historical demand simulation and intermittent demand forecasting are used in conjunction with a mixed integer linear program to determine optimal network nodal inventory policies. By varying demand characteristics and AM capacity this work assesses how to best employ AM capability within the network.FindingsThis research assesses the preferred AM-enabled supply chain configuration for varying levels of intermittent demand patterns and AM production capacity. The research shows that variation in demand patterns alone directly affects the preferred network configuration. The relationship between the demand volume and relative AM production capacity affects the regions of superior network configuration performance.Research limitations/implicationsThis research makes several simplifying assumptions regarding AM technical capabilities. AM production time is assumed to be deterministic and does not consider build failure probability, build chamber capacity, part size, part complexity and post-processing requirements.Originality/valueThis research is the first study to link realistic spare part demand characterization to AM supply chain design using quantitative modeling.

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