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

2021 ◽  
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 ◽  
Demand Patterns ◽  
The Impact

Purpose - 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/Approach - This 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. Findings - This 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/implications - This 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/value - This research is the first study to link realistic spare part demand characterization to AM supply chain design using quantitative modeling.

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.

Economic and Environmental Assessment of Spare Parts Production Using Additive Manufacturing

2019 ◽  
pp. 159-181
Author(s):  
Atanu Chaudhuri ◽  
Dennis Massarola
Keyword(s):  
Supply Chain ◽  
Additive Manufacturing ◽  
Dynamic Simulation ◽  
Environmental Sustainability ◽  
Selective Laser Sintering ◽  
Spare Part ◽  
Spare Parts ◽  
Logistics System ◽  
Supply Chain Costs ◽  
System Dynamic Simulation

This chapter aims to investigate the potential economic and environmental sustainability outcomes of additive manufacturing (AM) for spare parts logistics. System dynamic simulation was conducted to analyze the sustainability of producing a spare part used in a railways subsystem using a particular additive manufacturing (AM) technology (i.e., selective laser sintering [SLS]) compared to producing it using injection molding. The results of the simulation showed that using SLS for the chosen part is superior to the conventional one in terms of total variable costs as well as for carbon footprint. Compared to the conventional supply chain, for the AM supply chain, the costs of the supplier reduces by 46%, that of the railways company reduces by 71%, while the overall supply chain costs reduce by 61.9%. The carbon emissions in the AM supply chain marginally reduces by 2.89% compared to the conventional supply chain.

scholarly journals Impact of additive manufacturing on aircraft supply chain performance

2018 ◽  
Vol 29 (5) ◽  
pp. 846-865 ◽  
Author(s):  
Abhijeet Ghadge ◽  
Georgia Karantoni ◽  
Atanu Chaudhuri ◽  
Aravindan Srinivasan
Keyword(s):  
Supply Chain ◽  
Additive Manufacturing ◽  
Spare Part ◽  
Research Problem ◽  
Inventory Systems ◽  
Dynamics Simulation ◽  
Disruptive Technology ◽  
Content Type ◽  
Managerial Decisions ◽  
The Impact

Purpose The purpose of this paper is to assess the impact of additive manufacturing (AM) implementation on aircraft supply chain (SC) networks. Additive and conventional manufacturing spare part inventory control systems are studied and compared, revealing insights into SC performance. Design/methodology/approach A leading global commercial airline’s SC network data are used to model the research problem. A system dynamics simulation approach is followed, drawing out insights for managers. Findings A significant improvement in SC efficiency is observed through the implementation of AM, rendering it a worthwhile investment for global SCs. AM helps to balance inventory levels, and increase responsiveness while decreasing disruptions and carbon emissions in the supply networks. Practical implications The paper offers guidance on the adaption of AM in aircraft SCs and AM’s impact on spare part inventory systems. Originality/value The study provides robust evidence for making critical managerial decisions on SC re-design driven by a new and disruptive technology. Next-generation SC and logistics will replace the current demand for fulfilling material products by AM machines.

scholarly journals An integrated location-inventory model for a spare part’s supply chain considering facility disruption risk and CO2 emission

2021 ◽  
Vol 14 (2) ◽  
pp. 87
Author(s):  
Rubayet Karim ◽  
Koichi Nakade
Keyword(s):  
Supply Chain ◽  
Co2 Emission ◽  
Spare Part ◽  
Spare Parts ◽  
Inventory Model ◽  
Mixed Integer ◽  
Integer Programming Problem ◽  
Supply Chain Network ◽  
Emission Level ◽  
Disruption Risk

Purpose: Managing the inventory of spare parts is very difficult because of the stochastic nature of part’s demand. Also, only controlling the inventory of the spare part is not enough; instead, the supply chain of the spare part needs to be managed efficiently. Moreover, every organization now aims to have a resilient and sustainable supply chain to overcome the risk of facility disruption and to ensure environmental sustainability. This paper thus aims to establish a model of inventory-location relating to the resilient supply chain network of spare parts.Design/methodology/approach: First, applying queuing theory, a location-inventory model for a spare parts supply chain facing a facility disruption risk and has a restriction for CO2 emission, is developed. The model is later formulated as a non-linear mixed-integer programming problem and is solved using MATLAB.Findings: The model gives optimal decisions about the location of the warehouse facility and the policy of inventory management of each location selected. The sensitivity analysis shows that the very low probability of facility disruption does not influence controlling the average emission level. However, the average emission level certainly decreases with the increment of the disruption probability when the facility disruption probability is significant.Practical implications: Using this model, based on the cost and emission parameters and the likelihood of facility disruption, the spare part’s manufacturer can optimize the total average cost of the spare part’s supply chain through making a trade-off between productions, warehouse selection, inventory warehousing and demand allocation.Originality/value: Previous research focuses only on developing a framework for designing an efficient spare parts planning and control system. The inventory-location model for spare parts is not addressed in the sense of risk of facilities disturbance and emission. This research first time jointly considered the probabilistic facility disruption risk and carbon emission for modeling the spare part’s supply chain network.

scholarly journals Modeling and Optimization Sustainable Forest Supply Chain Considering Discount in Transportation System and Supplier Selection under Uncertainty

Forests ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 964
Author(s):  
Komeyl Baghizadeh ◽  
Dominik Zimon ◽  
Luay Jum’a
Keyword(s):  
Supply Chain ◽  
Working Hours ◽  
Mixed Integer ◽  
Forest Industry ◽  
Northern Iran ◽  
Suggested Approach ◽  
Tactical Decisions ◽  
Environmental Goals ◽  
Forest Supply Chain ◽  
The Impact

In recent decades, the forest industry has been growingly expanded due to economic conditions, climate changes, environmental and energy policies, and intense demand changes. Thus, appropriate planning is required to improve this industry. To achieve economic, social and environmental goals, a supply chain network is designed based on a multi-period and multi-product Mixed-Integer Non-Linear Programming (MINLP) model in which the objective is to maximize the profit, minimize detrimental environmental effects, improve social effects, and minimize the number of lost demands. In addition, to improve forest industry planning, strategic and tactical decisions have been implemented throughout the supply chain for all facilities, suppliers and machinery. These decisions significantly help to improve processes and product flows and to meet customers’ needs. In addition, because of the presence of uncertainty in some parameters, the proposed model was formulated and optimized under uncertainty using the hybrid robust possibilistic programming (HRPP-II) approach. The -constraint technique was used to solve the multi-objective model, and the Lagrangian relaxation (LR) method was utilized to solve the model of more complex dimensions. A case study in Northern Iran was conducted to assess the efficiency of the suggested approach. Finally, a sensitivity analysis was performed to determine the impact of important parameters on objective functions. The results of this study show that increasing the working hours of machines instead of increasing their number, increasing the capacity of some facilities instead of establishing new facilities and expanding the transport fleet has a significant impact on achieving predetermined goals.

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 Evaluating the Readiness Level of Additively Manufactured Digital Spare Parts: An Industrial Perspective

2018 ◽  
Vol 8 (10) ◽  
pp. 1837 ◽  
Author(s):  
Niklas Kretzschmar ◽  
Sergei Chekurov ◽  
Mika Salmi ◽  
Jukka Tuomi
Keyword(s):  
Additive Manufacturing ◽  
Manufacturing Industry ◽  
Spare Part ◽  
Spare Parts ◽  
Survey Study ◽  
Lead Times ◽  
Supply Networks ◽  
Readiness Level ◽  
End Use ◽  
Technological Limitations

Additive manufacturing of digital spare parts offers promising new possibilities for companies to drastically shorten lead times and to omit storage costs. However, the concept of digital spare parts has not yet gained much footing in the manufacturing industry. This study aims to identify grounds for its selective rejection. Conducted from a corporate perspective, outlining a holistic supply chain network structure to visualize different digital spare part distribution scenarios, this survey study evaluates technical and economic additive manufacturing capabilities. Results are analyzed and discussed further by applying the Mann-Whitney test to examine the influence of the company size and the presence of 3D-printed end-use components within supply networks on gathered data. Machines’ limited build chamber volumes and the necessity of post-processing are considered as the main technical challenges of current additive manufacturing processes. Furthermore, it can be concluded that company sizes have a significant effect on perceived technological limitations. Overall, the results lead to the conclusion that the readiness level of the digital spare parts concept demands for further development.

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.

scholarly journals Additive Manufacturing and Maritime Spare Parts: Benefits and Obstacles for the End-Users

2021 ◽  
Vol 9 (8) ◽  
pp. 895
Author(s):  
Evanthia Kostidi ◽  
Nikitas Nikitakos ◽  
Iosif Progoulakis
Keyword(s):  
Additive Manufacturing ◽  
New Technology ◽  
Spare Part ◽  
Spare Parts ◽  
Successful Implementation ◽  
Maritime Industry ◽  
End User ◽  
Space Reduction ◽  
Questionnaire Method ◽  
Industrial Context

3D printing or additive manufacturing (AM) (in the industrial context) is an innovative, as opposed to subtractive, technology, bringing new opportunities and benefits to the spare part supply chain (SPSC). The aim of this work is to capture the views of the stakeholders at the end of the chain, extruding factors that will benefit the end-user and the factors that are likely to be an obstacle, by employing the questionnaire method. Company objectives regarding spares (cost reductions, improvement of services, space reduction) have been prioritized differently by the stakeholders. The most important barriers according to the participants are the quality assurance of the spare parts made by the new technology followed by the know-how and skills of staff. Other views such as suitable parts are suggested. The practical value of this work, in addition to assessing the readiness of the industry, is that it provides guidance for the successful implementation of AM in the maritime industry.

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