Shorter Delivery Time Research Articles

Trading safety stock for service response time in inventory positioning

We study an inventory placement optimization problem where demand is sensitive to service response time, under the online retailing setting. The main challenge is to achieve the optimal trade‐off between revenue benefits from shorter delivery time and the increase in inventory cost associated with placing inventory closer to market demand. To predict the effects of modified demand under service response time variations, we introduce a demand prediction and elasticity model to quantify the sensitivity in demand for particular product categories. Of course, shortening response time by positioning products close to market demand may increase inventory costs. Hence, the team developed a novel data‐driven two‐stage stochastic programming approach complementing the demand prediction and elasticity model, which optimally trades safety stock with service response time and hence revenue increase. We then illustrate the impact of our approach through data provided by an e‐commerce retailer in North America. Our approach offers supply chain managers a general‐purpose decision support tool that optimizes the inventory network to generate recommended stocking levels for stores, distribution centers, and warehouses on a daily basis.

Novel Modification of the Collective Dynamic Routing Method for Sensors' Communication in Wi-Fi Public Networks.

The widespread use of the Internet of Things makes it relevant to use public IP networks for simultaneous access by both users and wireless sensors. To achieve this, a significant reduction in the subscriber devices' energy consumption is required. This paper analyzes the application features of the collective dynamic routing method both with and without the use of a robust method for estimating the channel data rate for sensors' communication in wireless public networks. Based on the analysis, a novel modification of the collective dynamic routing method has been developed that reduces the sensors' energy consumption while keeping a high data rate and short delivery time for users. An analysis of the network load, the total data transfer rate over the network, and the parameters affecting the sensors' energy consumption was carried out for a segment of a seamless IEEE 802.11ax network. The simulation demonstrated a high efficiency of using a novel modification of the collective dynamic routing method for access to users and wireless sensors.

Universal and dynamic ridge filter for pencil beam scanning particle therapy: a novel concept for ultra-fast treatment delivery

Objective. In pencil beam scanning particle therapy, a short treatment delivery time is paramount for the efficient treatment of moving targets with motion mitigation techniques (such as breath-hold, rescanning, and gating). Energy and spot position change time are limiting factors in reducing treatment time. In this study, we designed a universal and dynamic energy modulator (ridge filter, RF) to broaden the Bragg peak, to reduce the number of energies and spots required to cover the target volume, thus lowering the treatment time. Approach. Our RF unit comprises two identical RFs placed just before the isocenter. Both RFs move relative to each other, changing the Bragg peak’s characteristics dynamically. We simulated different Bragg peak shapes with the RF in Monte Carlo simulation code (TOPAS) and validated them experimentally. We then delivered single-field plans with 1 Gy/fraction to different geometrical targets in water, to measure the dose delivery time using the RF and compare it with the clinical settings. Main results. Aligning the RFs in different positions produces different broadening in the Bragg peak; we achieved a maximum broadening of 2.5 cm. With RF we reduced the number of energies in a field by more than 60%, and the dose delivery time by 50%, for all geometrical targets investigated, without compromising the dose distribution transverse and distal fall-off. Significance. Our novel universal and dynamic RF allows for the adaptation of the Bragg peak broadening for a spot and/or energy layer based on the requirement of dose shaping in the target volume. It significantly reduces the number of energy layers and spots to cover the target volume, and thus the treatment time. This RF design is ideal for ultra-fast treatment delivery within a single breath-hold (5–10 s), efficient delivery of motion mitigation techniques, and small animal irradiation with ultra-high dose rates (FLASH).

Project Attribute Information and Initiator’s Commitment in Crowdfunding Message Strategy: An Empirical Investigation of Financing Performance in Agri-Food Crowdfunding

Agri-food crowdfunding, a new financing method, not only solves the financing constraints in agricultural development, but also realizes the effective connection between agricultural products and the market. Thus, exploring the impact of project factors on financing performance can help initiators design scientific and reasonable crowdfunding project plans. Based on the trust theory and the elaboration likelihood model (ELM), the trust mechanism is constructed with the characteristic attributes as the central path, the competitive attributes as the edge path, and the commitment as the mediator. Using the data of 1166 agri-food crowdfunding projects on the Taobao crowdfunding platform, I investigate the impact of disclosed project attribute information on financing performance and the mediating role of project risk. The results show that projects with a detailed explanation of the crowdfunding reason and the capital uses, a low funding goal, product qualification certificates issued by authoritative institutions, multiple types of rewards, a short reward delivery time, and a low investment threshold achieve good financing performance. The factor of commitment plays an intermediary role in the relationship between project attributes and financing performance. Based on the research conclusions, practical enlightenment is proposed for initiators, crowdfunding platforms, and regulators.

Radiobiological Aspects of FLASH Radiotherapy.

Radiotherapy (RT) is one of the primary treatment modalities for cancer patients. The clinical use of RT requires a balance to be struck between tumor effect and the risk of toxicity. Sparing normal tissue is the cornerstone of reducing toxicity. Advances in physical targeting and dose-shaping technology have helped to achieve this. FLASH RT is a promising, novel treatment technique that seeks to exploit a potential normal tissue-sparing effect of ultra-high dose rate irradiation. A significant body of in vitro and in vivo data has highlighted a decrease in acute and late radiation toxicities, while preserving the radiation effect in tumor cells. The underlying biological mechanisms of FLASH RT, however, remain unclear. Three main mechanisms have been hypothesized to account for this differential FLASH RT effect between the tumor and healthy tissue: the oxygen depletion, the DNA damage, and the immune-mediated hypothesis. These hypotheses and molecular mechanisms have been evaluated both in vitro and in vivo. Furthermore, the effect of ultra-high dose rate radiation with extremely short delivery times on the dynamic tumor microenvironment involving circulating blood cells and immune cells in humans is essentially unknown. Therefore, while there is great interest in FLASH RT as a means of targeting tumors with the promise of an increased therapeutic ratio, evidence of a generalized FLASH effect in humans and data to show that FLASH in humans is safe and at least effective against tumors as standard photon RT is currently lacking. FLASH RT needs further preclinical investigation and well-designed in-human studies before it can be introduced into clinical practice.

Agricultural Based Drone

The main vison of our project is to built a drone which can do certain things that is very much impossible by standards of a human in the fields such as locomotion and aerodynamics. The demand for delivery personnel has multiplied due to the significant growth in the use of online ordering. In order to fulfil this demand, drone-based technology is being deployed. A hexacopter can fly vertically in a stable manner and be used to deliver goods or collect data in a certain area. We think delivery drones are poised to disrupt the last mile transportation industry given the development of drone technology and rising commercial usage. Drones can drastically shorten delivery times and lower the cost of delivery for both humans and drone manufacturers.. The value chain and opportunities in the market for delivery drones are examined in this paper. It also talks about adoption's difficulties. Our argument for using drones to deliver the majority of lightweight products for the final mile comes at the end. This study describes the Hexa copter (QC) as a lightweight, inexpensive, autonomous flying capable Unmanned Aerial Vehicle (UAV) for delivering packages ordered online. Its primary on-board computing unit is an android device. This QC can locate and reach its goal by using Google Maps. This experiment showcases QC's ability to deliver an online-ordered package and then return to the starting point. Future studies on the use of QC for parcel delivery are made possible by the method's encouraging results.

Optimization of the Delivery Time within the Distribution Network, Taking into Account Fuel Consumption and the Level of Carbon Dioxide Emissions into the Atmosphere

The evolution of changes in shopping in the modern society necessitates suppliers to seek new solutions consisting of increasing the efficiency of transport processes. When it comes to controlling the flow of goods in modern distribution networks, planning and timely deliveries are of particular importance. The first factor creating a competitive advantage involves the tendency to shorten order delivery times, especially for products with a short shelf life. Shorter delivery times, in turn, extend the period of effective residence of the product “available on the shelf”, increasing the likelihood of its sale. The second component in line with the Sustainable Development Strategy consists of aspects related to the protection of the natural environment, in particular those related to car transport. In this case, the fuel consumption and the level of emitted toxic substances (including carbon dioxide) are analyzed and assessed. Bearing in mind the above, this article presents the problem of optimizing the delivery time within the assumed distribution network and its solution, enabling the company to develop and optimal plan for the transport of products with a short shelf life. The paper proposes a model that takes into account minimization of the delivery time, while estimating the values of fuel consumption and CO2 emissions for the variants considered. The means of transport were medium-duty trucks. Three variants of the assumptions were considered, and algorithms implemented in MS Excel and MATLAB software were used to perform the optimization. Using the MATLAB environment, a more favorable value of the objective function was obtained for the variant without additional constraints. On the other hand, the algorithm implemented in MS Excel more effectively searched the set of acceptable solutions with a larger number of constraining conditions.

Analysis of Supply Chain Management Implementation on Amazon E-Commerce

Supply chain management itself provides a concept or mechanism that can increase the overall productivity of the company in the supply flow by optimizing the time, location, and flow of material quantities. Because one of the supply chain systems in question today is Amazon's e-commerce company, the purpose of this study is to find the implementation of a supply chain management system on Amazon's e-commerce. This research method uses a qualitative descriptive method by using relevant narratives from various trusted sources through websites or search. There are around 100 populations of E-commerce companies around the world in the 90s to 2022 with a total sample of 1 sample, namely the Amazon E-commerce company. The results show that Amazon has forced its competitors to increase aspects of supply chain automation, shorten delivery times, increase the number of warehouses, and engage in product manufacturing. With a combination of advanced information technology, extensive warehousing networks, multi-level inventory management, and reliable transportation, Amazon's supply chain is the world's most efficient leading company. There are six supply chain management applicable to Amazon e-commerce companies, namely- Outsourcing Inventory Management and Insourcing Logistics, Delivery Options To Customers, Push/Pull Strategy for Supply chain Success, Amazon's Warehouse Classes and Zones, Warehouse Automation and Supply Chain Cost.

A bi-objective optimization model for the medical supplies' simultaneous pickup and delivery with drones

In the COVID-19 pandemic, it is essential to transport medical supplies to specific locations accurately, safely, and promptly on time. The application of drones for medical supplies delivery can break ground traffic restrictions, shorten delivery time, and achieve the goal of contactless delivery to reduce the likelihood of contacting COVID-19 patients. However, the existing optimization model for drone delivery is cannot meet the requirements of medical supplies delivery in public health emergencies. Therefore, this paper proposes a bi-objective mixed integer programming model for the multi-trip drone location routing problem, which allows simultaneous pick-up and delivery, and shorten the time to deliver medical supplies in the right place. Then, a modified NSGA-II (Non-dominated Sorting Genetic Algorithm II) which includes double-layer coding, is designed to solve the model. This paper also conducts multiple sets of data experiments to verify the performance of modified NSGA-II. Comparing with separate pickup and delivery modes, this study demonstrates that the proposed optimization model with simultaneous pickup and delivery mode achieves a shorter time, is safer, and saves more resources. Finally, the sensitivity analysis is conducted by changing some parameters, and providing some reference suggestions for medical supplies delivery management via drones.

Treatment Planning for Cardiac Radioablation: Multicenter Multiplatform Benchmarking for the RAdiosurgery for VENtricular TAchycardia (RAVENTA) Trial

Cardiac radioablation is a novel treatment option for patients with refractory ventricular tachycardia unsuitable for catheter ablation. The quality of treatment planning depends on dose specifications, platform capabilities, and experience of the treating staff. To harmonize the treatment planning, benchmarking of this process is necessary for multicenter clinical studies such as the RAdiosurgery for VENtricular TAchycardia trial. Planning computed tomography data and consensus structures from 3 patients were sent to 5 academic centers for independent plan development using a variety of platforms and techniques with the RAdiosurgery for VENtricular TAchycardia study protocol serving as guideline. Three-dimensional dose distributions and treatment plan details were collected and analyzed. In addition, an objective relative plan quality ranking system for ventricular tachycardia treatments was established. For each case, 3 coplanar volumetric modulated arc (VMAT) plans for C-arm linear accelerators (LINAC) and 3 noncoplanar treatment plans for robotic arm LINAC were generated. All plans were suitable for clinical applications with minor deviations from study guidelines in most centers. Eleven of 18 treatment plans showed maximal one minor deviation each for target and cardiac substructures. However, dose-volume histograms showed substantial differences: in one case, the planning target volume ≥30 Gy ranged from 0.0% to 79.9% and the ramus interventricularis anterior V14Gy ranged from 4.0% to 45.4%. Overall, the VMAT plans had steeper dose gradients in the high-dose region, while the plans for the robotic arm LINAC had smaller low-dose regions. Thereby, VMAT plans required only about half as many monitor units, resulting in shorter delivery times, possibly an important factor in treatment outcome. Cardiac radioablation is feasible with robotic arm and C-arm LINAC systems with comparable plan quality. Although cross-center training and best practice guidelines have been provided, further recommendations, especially for cardiac substructures, and ranking of dose guidelines will be helpful to optimize cardiac radioablation outcomes.

Pumps as Turbines (PATs) by Analysis with CFD Models

Pumps as turbines (PATs) are the typical solution for electrification using micro hydropower plants (MHP) in the rural sector. Other engineering applications where lately the use of PATs have increased are irrigation, water supply, and energy recovery systems due to their availability, short delivery time, long service life, economic feasibility, construction, and maintenance advantages. However, selecting the suitable pump(s) is difficult because manufacturers only provide performance curves when operating in pump mode; therefore, there is no universal method to predict that issue. For this reason, theoretical, analytical, experimental, and numerical simulation research have been made to predict these curves and the PATs' performance. The present paper analyzes PATs with Computational Fluid Dynamics (CFD) based on advanced research. For this aim, information from a wide range of types of pumps with different rotation speeds was classified to examine case approaches, computational domains, mesh generation, boundary conditions, optimization of elements, and CFD package used to establish the effectiveness of this tool and to find characteristics which have not been enough investigated at present. Most studies used CFD simulations with ANSYS code and K- turbulence closure model, which presented adequate results. Finally, this paper shows that numerical simulations with CFD analysis were successfully carried out to determine pump performance and predict curves in direct and reverse mode, improving certain components and conducting more profound research on certain specific issues.

A Review Analysis of Design Models for Mechatronic Product Design Perspectives

The design of a mechatronic system is considered according to the concurrent engineering approach within the framework of a development cycle, is a methodological approach to master the design of complex systems and products. Competition on product quality and performance has become the main factor that companies face in today's market. These pressures are driving technological advances to provide systems with a constant increase in performance at reduced costs and in shorter delivery times. The performance includes better interoperability, improved reliability, good safety and smaller size that have determined the birth of mechatronic systems. Obtaining a product with these qualities in a reduced time would be beneficial for design companies if they follow an efficient design model appropriate for complex system. In this context, this paper conducts a discretized study on the main mechatronic design patterns in order to make their use understandable for the design of mechatronic products. Another essential aspect of the work lies on the comparison of the different existing design models analyzed on the basis of the multi-criteria analysis according to some fixed criteria in order to present a comparative study for choosing a better model for mechatronic product design perspectives.

Forecasting of Musical Equipment Demand Based on a Deep Neural Network

With the popularity of music, the music equipment market has ushered in a new round of explosion. But at the same time, the market environment is changing rapidly, and music equipment companies are greatly affected by market changes. This type of enterprise has a wide variety of products, fast update, short delivery time and urgent time, which is a severe challenge to its production and operation. In this environment, in order to quickly respond to changes in the market environment, and to formulate plans for corporate procurement, production, and sales in an orderly manner, music equipment companies must make accurate predictions of market demand. At present, the extended research based on LSTM is a relatively mainstream deep neural network in the research methods of time series problems. This article is based on LSTM model to conduct an in-depth study on the prediction of music equipment demand. In order to solve the problems of overfitting, disappearance of gradient, model collapse and other problems in previous experimental studies, this paper proposes an improved LSTM prediction model. In terms of model structure selection, Dropout mechanism is used, and L2 regular term is introduced. In the selection of the activation function, MReLU function is proposed, which can improve the prediction effect of the model and enhance the applicability of the model. To measure the prediction effect of the improved LSTM model established in this paper, this paper selects RMSE and MAE as evaluation indicators, and compares experiments with other mainstream prediction models. The research results show that the improved LSTM network prediction model is superior to other models in the prediction of music equipment demand, which verifies the effectiveness.

МІЖНАРОДНИЙ ТРАНСПОРТНО-ЛОІГСТИЧНИЙ БІЗНЕС В СИСТЕМІ МІЖНАРОДНОЇ ЕКОНОМІЧНОЇ БЕЗПЕКИ

The article analyzes the current trends of the international transport and logistics business in the system of international economic security. The development of the integration of the world economy and the globalization of business contribute to the creation of international logistics systems and global supply chains. The article highlights the main directions of increasing the efficiency of supply chain management and indicates the sources of increasing the efficiency of this process. The key negative aspects that prevent the effective functioning of international transport and logistics systems have been identified. A comparison is made between the traditional approach to production and the logistic approach, when the manufacturer starts production only when a specific order is received. The inventory management system of the seller is characterized. An overview of modern trends in the international transport and logistics business was carried out, in particular: increasing turnover while shortening delivery times, increasing investments in logistics startups by venture funds, customization, the use of multimodal transport and logistics centers, ecological logistics, etc. The main directions in which digital logistics centers can help logistics companies to achieve success are determined, in particular, it was determined that success will be achieved through the use of the method of «postponement» or «delayed product differentiation», the organization of e-commerce logistics, containerization, increasing the share of direct express deliveries from the producer to the consumer, bypassing intermediaries and intermediate warehouses, electronic exchange of data and various information, the growth of the agricultural machinery market, the use of multimodal transport and logistics centers, as well as clear planning of supply chains, flexibility, management of stocks and volumes. Also, a hypothesis was put forward about the emergence of a new term «logtech company», which includes not only the creation of new technologies, but also new logistics business models based on the joint use (shared use) of transportation.

Mathematical Justification of the Optimal Option for Accelerated Cargo Transportation Organization

Today, among the main requirements of customers to the conditions of cargo transportation by rail is a shortened delivery time. In this regard, one of the most promising and sought-after areas of improvement in rail transportation is the organization of accelerated freight delivery services that can compete with road transportation both in terms of delivery speed and transportation cost, and in terms of departure regularity. However, the formation of an accelerated train requires a large batch of cargo, which is quite difficult to collect at a single departure station, and the accumulation of cargo for several days reduces the demand for accelerated delivery due to the irregularity of the train. To solve this problem, it is proposed to have stop-offs on the way of the train, replenishing the train with cars that require expedited delivery. In this case, the task is to choose the number of stops and the number of cars, comparing the income from the service and the cost of the stop, to maximize profits. This paper presents a mathematical model made by the authors, which describes the proposed method of transportation organization and provides comparing income and expenses components formed when implementing a train service with stop-offs on the way for the transfer of rolling stock, as well as the analysis of the studies carried out with its application.

Eş ve Anne/Arkadaş Desteğinin Doğum Sürecine Etkisi: Karşılaştırmalı Tanımlayıcı Araştırma

Objective: This research was conducted to examine the effect of spouse, mother/friend and routine clinical care support on delivery process at birth. Material and Methods: This descriptive/cross-sectional study was completed with 300 primipara pregnant women who applied to İstanbul Esenler Gynecology and Pediatrics Hospital. Participants are divided into 3 groups according to the people they want to be there for support. The first group is spouse support, the second group is mother/friend support and the third group is women who want routine clinical care. In the collection of the data, personal information form and Visual Analog Scale (fear/anxiety, coping with pain, birth satisfaction) developed by the researchers in line with the literature were used. Results: In the transition phase of labor, anxiety score was lower in the group receiving spouse support (7.08±0.88) compared to the mother/friend (8.74±0.65) and the control group (8.72±0.65) (p<0.00). The lowest score in coping with pain in the transition phase (1.83±0.57) was in the group receiving routine clinical care. The delivery time of the group receiving routine clinical care (298.00±32.22 minute) was longer than the group receiving spousal support and mother/friend support (p<0.05). Conclusion: Spouse support at birth decreases anxiety, increases coping with pain and shortens delivery time. Spousal support for eligible women can improve their delivery process. Midwives should be empowered to provide supportive care and be more effective in coping with pain.

A Study on Parcel Locker Location Problem in Last Mile Delivery

As the EC markets are expanding, customers are increasingly demanding small lots and short delivery times. The need for efficient, fast, and convenient last mile delivery will likely continue to grow. One of the problems with the last mile delivery in supply chain management is the frequent redelivery of parcels due to the absence of consumers. Therefore, the use of parcel lockers can be expected to be significantly effective in reducing redeliveries. This research proposes a method for deciding parcel locker locations, which highly convenient not only for consumers but also for delivery companies from the viewpoint of minimizing both the detour distance from consumers’ travelling routes and the delivery distance of delivery companies. Numerical experiments are carried out by using road information obtained from detailed map data in order to evaluate the effectiveness of the proposed method.

Evaluating robot bin-picking performance based on Box and Blocks Test

The rise of e-commerce, which demands solutions for small order sizes, large product assortment, short delivery times, and variable order quantity has created a need for more advanced warehousing and order-picking systems. The advancements in collaborative robotics have made it possible to automate intralogistics processes, especially the order-picking systems. If the items to be order-picked are stored in small containers, called bins, the process is known as bin-picking. The processes of bin-picking are still mainly manual due to the adaptability, dexterity, and pace of human hands. However, with the emerging technologies, the gap between human and robot dexterity is getting thinner. The integrators of robotic technologies are therefore faced with the challenge of choosing an appropriate robotic system for bin-picking. There is a lack of standardized procedures, which are designed to process such decisions easier. In our research paper, we propose an improved robotic version of the Box and Blocks Test (BBT), which provides a quick evaluation of a complete robotic bin-picking system. Using our improved robot-adapted BBT protocol, we evaluate a sample robotic bin-picking system, consisting of a collaborative robot, a 3D vision system and three types of robotic grippers, comparing the bin-picking performance of each configuration.

Dwell Time Analysis of Clearing Import Cargo in India

In a competitive global world, a short delivery time is of utmost value. Looking from the importing country’s administrative perspective, the time taken from the arrival of cargo into ports/ airports to being cleared by customs authorities is of key importance in the overall delivery time. This article analyses the dwell time (DT) performance of cargo imported into India and consists of two groups: sea cargo and air cargo. Evaluation of the current performance in comparison with goals set in the National Trade Facilitation Action Plan (NTFAP) of India 2017–2020, under World Trade Organization (WTO) agreement on Trade Facilitation Agreement (TFA) is conducted. To give out recommendations for reduction in DT, the channel of clearance and location of the custom site is studied independently and in combination. Dwell time, Import clearance process, Channel of clearance

"TORRESPRINT3D® - NEW ADDITIVE MANUFACTURING PROCESS FOR LARGE COMPONENTS"

Additive manufacturing (AM) for large volume parts is a rising technology with the potential to reduce the fabrication costs and lead times for components. It has practical applications in multiple industrial fields. AM technology can be instrumental in producing large pieces with complex geometries, especially for tooling and ancillary equipment. Despite these advantages, several technological aspects limit the use of AM for massive manufacturing. One of the limitations is the need to maintain the part and the working area at an elevated temperature using heating systems. Another critical limitation is the size of the 3D printing system, limiting the size of the components that can be produced using this technology and imposing some restrictions regarding the components&rsquo; geometry and thickness. Research has been carried out to solve these primary issues, and specific solutions have been developed and matured. The solution shown on this article comprises: 1. A system that can alter the required temperature locally without using a heated working environment 2. A moving base that supports the part during the manufacturing process eliminates the part dimension&rsquo;s limits, allowing for the manufacture of large -&ldquo;infinite&rdquo;- parts 3. The material applying process design allows depositing the material increased flexibility and perfect control of the thickness and layer overlap. These new technologies have been tested extensively by manufacturing and testing large industrial molds obtaining excellent results. The fields of application of this technology are limitless. The principal industries that can benefit from immediate uses are the aerospace, wind energy, naval, and railway sectors. This technology will revolutionize the mold manufacturing industry, allowing the curing mold manufacturers to produce large curing molds at a low cost and shorter delivery times.