Delivery Time Research Articles

Performance Analysis of Automated Parcel Lockers in Urban Delivery: Combined Agent-Based–Monte Carlo Simulation Approach

Background: The habitat structure, the environmental impact, the market acceptance, the changes in consumers’ preferences, and the pandemic urged for innovative solutions in urban last-mile delivery. Parcel lockers are among the most preferred solutions by customers due to their home proximity, time availability, and cost efficiency. Methods: This paper introduces an agent-based model (ABM) and a Monte Carlo simulation program to analyze in detail the activity of parcel locker points. The ABM describes the behavior of the agents (customers, parcels, lockers, delivery agents). The simulation is realized using ARENA 12 software. Two scenarios are created based on the number of daily delivery shifts; for each scenario, 300 simulation experiments with various input data are conducted. Results: Three measures of performance (MOPs) are selected to assess the system activity: the number of daily delivered parcels, the delivery time of an order, and the daily delayed orders. The simulation outputs reveal significant predictors of MOPs and disclose moments when actions need to be taken to increase system capacity or change customer behavior. Conclusions: The versatility of the simulation model in terms of input variables makes it a useful decision support tool for planning by highlighting quantitative assessments, organizing delivery activity, along with influences due to customer behavior changes.

Online scheduling problem of incompatible batch processing with deterioration effect and delivery time in the steel rolling process

As market competition intensifies, modern enterprises prioritize customer demands, leading to an increased emphasis on multi-variety and small-batch production. In this article, we study the online scheduling problem for incompatible batch processing with the deterioration effect to minimize the maximum delivery completion time in the billet rolling process, where the batch capacity and delivery capacity are unbounded. We assume that the processing time of job Jj is expressed as p j = a j ( A + Bt ) , where A > 0, B > 0, t denotes the start time of job and aj > 0 represents the job’s processing deterioration rate. For such an online problem, we first prove that the lower bound of the problem is ( 1 + B a max ) k , where k denotes the number of job families and a max represents the maximum deterioration ratio in job instance. Then we design an online algorithm Largest Delivery Time With Batch Processing and demonstrate that the competitive ratio of the algorithm is no more than 1 + ( 1 + B a max ) k . Finally, experiments on randomly generated instances prove that our algorithm is reasonable and effective.

Fulfillment of Permanent Contraception among Patients with Cesarean Delivery in a Multi-Site Cohort.

This study aimed to assess the association between insurance type and permanent contraception fulfillment among those with cesarean deliveries. Additionally, we sought to examine modification by the scheduled status of the cesarean. We used data from a multi-site cohort study of patients who delivered in 2018-2019 at Northwestern Memorial Hospital in Illinois, MetroHealth Medical System in Ohio, or University of Alabama at Birmingham in Alabama. All patients had permanent contraception as their contraceptive plan in their medical chart during delivery hospitalization. We used logistic regression to model the association between insurance type, scheduled status of cesarean and permanent contraception fulfillment by hospital discharge. The scheduled status of cesarean delivery was examined as an effect modifier. Compared to patients with private insurance, those with Medicaid were less likely to have their desired permanent contraception procedure fulfilled by hospital discharge (89.3% vs. 96.8%, p < 0.001). After adjusting for covariates, patients with Medicaid had a lower odds of permanent contraception fulfillment by hospital discharge (OR: 0.41; 95% CI: 0.21, 0.77). This association was stronger among those who had unscheduled cesarean deliveries (OR: 0.29; 95% CI: 0.12, 0.74) than those with scheduled cesarean deliveries (OR: 0.77; 95% CI: 0.32, 1.88). Compared to patients with private insurance undergoing a cesarean delivery, those with Medicaid insurance were less likely to have their desired permanent contraception fulfilled. Physicians and hospitals must examine their practices surrounding Medicaid forms to ensure that patients have valid consent forms available at the time of delivery.

A semiconductor wafer manufacturing system scheduling start-up and decision mechanism considering bottleneck drift characteristics

The development of Artificial Intelligence (AI) requires a significant amount of high-performance semiconductor chips. Scientifically and effectively scheduling and optimizing semiconductor wafer manufacturing systems can improve the productivity of the production system, equipment utilization, and semiconductor chip output. Therefore, scheduling optimization and decision-making for semiconductor wafer manufacturing systems have become a hot research topic for current researchers. However, bottleneck drift is an important feature of semiconductor wafer manufacturing systems, and is also a key factor that constrains scheduling and decision-making in semiconductor wafer manufacturing systems. Currently, there is a lack of research on the specific characteristics of bottleneck drift in semiconductor wafer manufacturing systems in the literature, which leads to problems such as ineffective planning and scheduling decisions by managers, and affects the performance of semiconductor wafer manufacturing systems. This paper considers the triggering conditions, occurrence time, and impact on production plan objectives of bottleneck drift, and improves two methods for bottleneck identification and bottleneck drift, based on which a new semiconductor wafer manufacturing systems scheduling start-up mechanism is proposed, which includes three parts and nine steps. Firstly, the semiconductor wafer manufacturing system scheduling process is given, including bottleneck identification, impact analysis, prediction, and planning for the impact of bottleneck drift on production plan objectives. Secondly, bottleneck identification and impact factors are predicted based on bottleneck drift, and the trigger conditions and drift time of bottleneck drift are determined. Then, based on the delivery time of the production plan objectives, the impact of bottleneck drift on production plan objectives is analyzed to determine the scheduling start-up conditions for the semiconductor wafer manufacturing system. Experimental results show that the mechanism proposed in this paper can timely and accurately identify the triggering conditions and drift time of bottleneck drift, avoid ineffective scheduling decisions before bottleneck drift, avoid unnecessary production scheduling decisions, and reduce additional performance losses. In addition, it can analyze the impact of bottleneck drift on production plan objectives according to the production plan objectives, so as to formulate scheduling decision-making schemes better, avoiding production plan delays and waste of production capacity.

Single institution experience of MRI-guided radiotherapy for thoracic tumors and clinical characteristics impacting treatment duty cycle.

MRI-guided radiotherapy (MRgRT) allows for direct motion management and real-time radiation treatment plan adaptation. We report our institutional experience using low strength 0.35T MRgRT for thoracic malignancies, and evaluate changes in treatment duty cycle between first and final MRgRT fractions. All patients with intrathoracic tumors treated with MRgRT were included. The primary reason for MRgRT (adjacent organ at risk [OAR] vs. motion management [MM] vs. other) was recorded. Tumor location was classified as central (within 2cm of tracheobronchial tree) vs. non-central, and further classified by the Expanded HILUS grouping. Gross tumor volume (GTV) motion, planning target volume expansions, dose/fractionation, treatment plan time, and total delivery time were extracted from the treatment planning system. Treatment plan time was defined as the time for beam delivery, including multileaf collimator (MLC) motion, and gantry rotation. Treatment delivery time was defined as the time from beam on to completion of treatment, including treatment plan time and patient respiratory breath holds. Duty cycle was calculated as treatment plan time/treatment delivery time. Duty cycles were compared between first and final fraction using a two-sample t-test. Twenty-seven patients with thoracic tumors (16 non-small cell lung cancer and 11 thoracic metastases) were treated with MRgRT between 12/2021 and 06/2023. Fifteen patients received MRgRT due to OAR and 11 patients received MRgRT for motion management. 11 patients had central tumors and all were treated with MRgRT due to OAR risk. The median dose/fractionation was 50 Gy/5 fractions. For patients treated due to OAR (n=15), 80% had at least 1 adapted fraction during their course of radiotherapy. There was no plan adaptation for patients treated due to motion management (n=11). Mean GTV motion was significantly higher for patients treated due to motion management compared to OAR (16.1mm vs. 6.5mm, p=0.011). Mean duty cycle for fraction 1 was 54.2% compared to 62.1% with final fraction (p=0.004). Mean fraction 1 duty cycle was higher for patients treated due to OAR compared to patients treated for MM (61% vs. 45.0%, p=0.012). Duty cycle improved from first fraction to final fraction possibly due to patient familiarity with treatment. Duty cycle was improved for patients treated due to OAR risk, likely due to more central location and thus decreased target motion.

Correlating maternal and cord-blood inflammatory markers and BDNF with human fetal brain activity recorded by magnetoencephalography: An exploratory study

BackgroundDuring gestation, the brain development of the fetus is affected by many biological markers, where inflammatory processes and neurotrophic factors have been of particular interest in the past decade. AimThis exploratory study is the first attempt to explore the relationships between biomarker levels in maternal and cord-blood samples and human fetal brain activity measured with non-invasive fetal magnetoencephalography (fMEG). MethodTwenty-three women were enrolled in this study for collection of maternal serum and fMEG tracings immediately prior to their scheduled cesarean delivery. Twelve of these women had a preexisting diabetic condition. At the time of delivery, umbilical cord blood was also collected. Biomarker levels from both maternal and cord blood were measured and subsequently analyzed for correlations with fetal brain activity in four frequency bands extracted from fMEG power spectral densities. ResultsRelative power in the delta, alpha, and beta frequency bands exhibited moderate-sized correlations with maternal BDNF and cord-blood CRP levels before and after adjusting for confounding diabetic status. These correlations were negative for the delta band, and positive for the alpha and beta bands. Maternal CRP and cord-blood BDNF and IL-6 exhibited negligible correlations with relative power in all four bands. Diabetes did not appear to be a strong confounding factor affecting the studied biomarkers. ConclusionsMaternal BDNF levels and cord-blood CRP levels appear to have a direct correlation to fetal brain activity. Our findings indicate the potential use of these biomarkers in conjunction with fetal brain electrophysiology to track fetal neurodevelopment.

Cardinality-constrained plan-quality and delivery-time optimization method for proton therapy.

While minimizing plan delivery time is beneficial for proton therapy in terms of motion management, patient comfort, and treatment throughput, it often poses a tradeoff with optimizing plan quality. A key component of plan delivery time is the energy switching time, which is approximately proportional to the number of energy layers, that is, the cardinality. This work aims to develop a novel optimization method that can efficiently compute the pareto surface between plan quality and energy layer cardinality, for the planner to navigate through this quality-and-efficiency tradeoff and select the appropriate plan of a balanced tradeoff. A new IMPT method CARD is proposed that (1) explicitly incorporates the minimization of energy layer cardinality as an optimization objective, and (2) automatically generates a set of plans sequentially with a descending order in number of energy layers. The energy layer cardinality is penalized through the l1,0-norm regularization with an upper bound, and the upper bound is monotonically decreased to compute a series of treatment plans with gradually decreased energy layer cardinality on the quality-and-efficiency pareto surface. For any given treatment plan, the plan optimality is enforced using dose-volume planning objectives and the plan deliverability is imposed through minimum-monitor-unit (MMU) constraints, with optimization solution algorithm based on iterative convex relaxation. The new method CARD was validated in comparison with the benchmark plan of all energy layers (P0), and a state-of-the-art method called MMSEL, using prostate, head-and-neck (HN), lung, pancreas, liver and brain cases. While labor-intensive and time-consuming manual parameter tuning was needed for MMSEL to generate plans of predefined energy layer cardinality, CARD automatically and efficiently computed all plans with sequentially decreasing predefined energy layer cardinality all at once. With the acceptable plan quality (i.e., no more than 110% of total optimization objective value from P0), CARD achieved the reduction of number of energy layers to 52% (from 77 to 40), 48% (from 135 to 65), 59% (from 85 to 50), 67% (from 52 to 35), 80% (from 50 to 40), and 30% (from 66 to 20), for prostate, HN, lung, pancreas, liver, and brain cases, respectively, compared to P0, with overall better plan quality than MMSEL. Moreover, due to the nonconvexity of the MMU constraint, CARD provided the similar or even smaller optimization objective than P0, at the same time with fewer number of energy layers, that is, 55 versus 77, 85 versus 135, 45 versus 52, and 25 versus 66 for prostate, HN, pancreas, and brain cases, respectively. We have developed a novel optimization algorithm CARD that can efficiently and automatically compute a series of treatment plans of any given energy layer sequentially, which allows the planner to navigate through the plan-quality and energy-layer-cardinality tradeoff and select the appropriate plan of a balanced tradeoff.

Family Support to Women During Pregnancy and Its Impact on Maternal and Fetal Outcomes.

Family support is one of the determinants of lifestyle habits and relevant health behavior for pregnancy outcomes. In India, the joint family system is still practiced. Due to education, urbanization, and industrialization, the family institution continues to play a central role in people's lives.Pregnancy is a crucial period in women's lives. Good care during pregnancy is important for the health of the mother and the newborn baby. During this period, hormonal changes are complex and involve multiple hormones working together to support the developing fetus and prepare the mother's body for labor, delivery, and breastfeeding. To avoid maternal and fetal complications, she needs support from her family throughout pregnancy and the postnatal period. This study aims to evaluate the influence of the level and quality of family support during pregnancy on maternal and fetal outcomes and to identify any association between the sociodemographic variables and the impact of the level and quality of family support during the first trimester. This study used a quantitative approach with a survey research design. Data were collected from four Primary Health Centers at Karad, Maharashtra, India, i.e., Rethare, Vadgaon, Kale, and Supane. A consecutive sampling technique was used to select the 344 subjects from the Rethare, Vadgaon, Kale, and Supane areas of Karad Taluka. Data were collected before the completion of the first three months of pregnancy, then during the second trimester and after delivery. Upon evaluation, the tool was validated by experts representing a range of specialties, including community health nursing, mental health nursing, obstetric gynecology, and pediatric care. A pilot study was conducted on 30 samples. The data collected were analyzed by using descriptive and inferential statistics. The findings of the study show a significant association between the psychosocial support received in the first trimester and the total gestational weeks completed at the time of delivery (p < 0.05). The study suggests the need for psychosocial support during the first trimester for better maternal and fetal outcomes. Psychosocial family support is needed by pregnant women during the first trimester to achieve maternal and fetal outcomes.

The generator distribution problem for base stations during emergency power outage: A branch-and-price-and-cut approach

Motivated by the need for uninterrupted service provision in the telecommunications industry, this paper presents a novel problem concerning the transportation of diesel generators during an unplanned power outage. Given a set of base stations, each equipped with a capacitated back-up battery pack, the problem consists in finding an optimal delivery and pick-up schedule that minimises corresponding costs. The problem is significantly complicated by the fact that the delivery quantity is a decision variable, and the pick-up times depend on the delivery time, delivery quantity and constraints related to battery-charging requirements. To address the issue, we develop problem-specific pick-up time functions that can be effectively incorporated into the proposed algorithm. The problem is formulated as an arc-based model and a set-packing model. To solve it to optimality, we design a tailored branch-and-price-and-cut algorithm, including novel customised dominance criteria in the labelling algorithm and adopting heuristics that exploit the problem features and effectively improve the algorithmic performance. The efficacy of the proposed algorithm is validated based on the extensive computational study and compared with a commercial solver. The proposed acceleration techniques are found to be potent with regard to computational times, and useful managerial insights are provided as part of sensitivity analyses.

LLIN Evaluation in Uganda Project (LLINEUP): modelling the impact of COVID-19-related disruptions on delivery of long-lasting insecticidal nets on malaria indicators in Uganda

BackgroundDisruptions in malaria control due to COVID-19 mitigation measures were predicted to increase malaria morbidity and mortality in Africa substantially. In Uganda, long-lasting insecticidal nets (LLINs) are distributed nationwide every 3–4 years, but the 2020–2021 campaign was altered because of COVID-19 restrictions so that the timing of delivery of new nets was different from the original plans made by the National Malaria Control Programme.MethodsA transmission dynamics modelling exercise was conducted to explore how the altered delivery of LLINs in 2020–2021 impacted malaria burden in Uganda. Data were available on the planned LLIN distribution schedule for 2020–2021, and the actual delivery. The transmission model was used to simulate 100 health sub-districts, and parameterized to match understanding of local mosquito bionomics, net use estimates, and seasonal patterns based on data collected in 2017–2019 during a cluster-randomized trial (LLINEUP). Two scenarios were compared; simulated LLIN distributions matching the actual delivery schedule, and a comparable scenario simulating LLIN distributions as originally planned. Model parameters were otherwise matched between simulations.ResultsApproximately 70% of the study population received LLINs later than scheduled in 2020–2021, although some areas received LLINs earlier than planned. The model indicates that malaria incidence in 2020 was substantially higher in areas that received LLINs late. In some areas, early distribution of LLINs appeared less effective than the original distribution schedule, possibly due to attrition of LLINs prior to transmission peaks, and waning LLIN efficacy after distribution. On average, the model simulations predicted broadly similar overall mean malaria incidence in 2021 and 2022. After accounting for differences in cluster population size and LLIN distribution dates, no substantial increase in malaria burden was detected.ConclusionsThe model results suggest that the disruptions in the 2020–2021 LLIN distribution campaign in Uganda did not substantially increase malaria burden in the study areas.

Reducing alcohol harms whilst minimising impact on hospitality businesses: ‘Sweetspot’ policy options

BackgroundDuring COVID-19, hospitality businesses (e.g. bars, restaurants) were closed/restricted whilst off-sales of alcohol increased, with health consequences. Post-covid, governments face lobbying to support such businesses, but many health services remain under pressure. We appraised ‘sweetspot’ policy options: those with potential to benefit public services and health, whilst avoiding or minimising negative impact on the hospitality sector. MethodsWe conducted rapid non-systematic evidence reviews using index papers, citation searches and team knowledge to summarise the literature relating to four possible ‘sweetspot’ policy areas: pricing interventions (9 systematic reviews (SR); 14 papers/reports); regulation of online sales (1 SR; 1 paper); place-shaping (2 SRs; 18 papers/reports); and violence reduction initiatives (9 SRs; 24 papers/reports); and led two expert workshops (n = 11). ResultsInterventions that raise the price of cheaper shop-bought alcohol appear promising as ‘sweetspot’ policies; any impact on hospitality is likely small and potentially positive. Restrictions on online sales such as speed or timing of delivery may reduce harm and diversion of consumption from on-trade to home settings. Place-shaping is not well-supported by evidence and experts were sceptical. Reduced late-night trading hours likely reduce violence; evidence of impact on hospitality is scant. Other violence reduction initiatives may modestly reduce harms whilst supporting hospitality, but require resources to deliver multiple measures simultaneously in partnership. ConclusionsAvailable evidence and expert views point to regulation of pricing and online sales as having greatest potential as ‘sweetspot’ alcohol policies, reducing alcohol harm whilst minimising negative impact on hospitality businesses.

A Knowledge-Guided Multi-Objective Shuffled Frog Leaping Algorithm for Dynamic Multi-Depot Multi-Trip Vehicle Routing Problem

Optimization algorithms have a wide range of applications in symmetry problems, such as graphs, networks, and pattern recognition. In this paper, a dynamic periodic multi-depot multi-trip vehicle routing model for scheduling test samples is constructed, which considers the differences in testing unit price and testing capacity of various agencies and introduces a cross-depot collaborative transport method. Both the cost and the testing time are minimized by determining the optimal sampling routes and testing agencies, subjecting to the constraints of vehicle capacity, number of vehicles, and delivery time. To solve the model, a knowledge-guided multi-objective shuffled frog leaping algorithm (KMOSFLA) is proposed. KMOSFLA adopts a convertible encoding mechanism to realize the diversified search in different search spaces. Three novel strategies are designed: the population initialization with historical information reuse, the leaping rule based on the greedy crossover and genetic recombination, and the objective-driven enhanced search. Systematic experimental studies are implemented. First, feasibility analyses of the model are carried out, where effectiveness of the cross-depot collaborative transport is validated and sensitivity analyses on two parameters (vehicle capacity and proportion of the third-party testing agencies) are performed. Then, the proposed algorithm KMOSFLA is compared with five state-of-the-art algorithms. Experimental results indicate that KMOSFLA can provide a set of non-dominated schedules with lower cost and shorter testing time in each scheduling period, which provides a reference for the dispatcher to make a final decision.

Pricing, channel design, and platform operations with buy-online-and-pick-up-in-store in online food delivery market

Omnichannel selling has gradually become popular in recent years, and the booming online food delivery (OFD) industry is no exception. Buy online and pick up in-store (BOPS) is regarded as the most important omnichannel fulfilment strategy. In this paper, we establish a stylised model to analyse the effects of BOPS on customer purchases and merchant profitability in the OFD market. We also examine merchants’ pricing and channel design strategies and the operational management of OFD platforms. We consider two merchant segments: online-only merchants who sell products only online and omni-merchants who sell products both online and offline. Interestingly, we find that BOPS helps online-only merchants expand market coverage, but does not necessarily increase omni-merchants’ sales depending on the delivery time and delivery service fee. Furthermore, online-only merchants should always implement BOPS, while omni-merchants should be more cautious about implementing BOPS because it may hurt their profits. In addition, the OFD platform charges a higher delivery service fee under certain conditions to react to merchants’ strategic adoption of BOPS. Finally, the adoption of BOPS may benefit merchants, customers, and platforms simultaneously. Therefore, BOPS may alleviate the contradictions among players in the OFD market.

Drone-Based Instant Delivery Hub-and-Spoke Network Optimization

Drone-based transportation is emerging as a novel mode in city logistics, featuring first-mile pickup and last-mile instant delivery using drones and truck transshipment. A fundamental challenge involves coordinating merchants, drones, transshipment hubs, trucks, and consumer communities through the hub-and-spoke network (HSN). This study formulated the optimization problem for HSN to minimize logistics costs and loss of orders constrained by service time limits. The ε-constraint model, two evolutionary algorithms based on Non-dominated Sorting Genetic Algorithm II (NSGA-II) using permutation (EAp) and rand key-based (EAr) encoding/decoding schemes were devised to solve the bi-objective mathematical program. Three groups of twelve experiments were conducted using ideal datasets and datasets generated from Shenzhen city to validate the models and algorithms. Relaxing the logistics objective by 10% and subsequently minimizing the loss of orders can significantly reduce average unmet orders by 24.61%; when spokes were beyond 20, the ε-constraint model failed to achieve solutions within an acceptable time. While EAp and EAr demonstrated competence, EAr proved to be more competitive in computation time, hypervolume, spacing metric, and the number of non-dominated solutions on the Pareto fronts. Key parameters influencing the HSN solutions include drone and truck speeds, acceptable delivery times, and the processing and waiting time at hubs.

Examining the Retail Delivery Choice Behavior in a Technology-Aware Market

This study aims to provide valuable insights into consumer preferences for delivery services in online shopping in Chile. The COVID-19 pandemic has accelerated the evolution of delivery and logistics services, leading to increased competition among online stores. Chile, with its highly digitally enabled population and a competitive landscape of online retailers, serves as an ideal reference case for Latin America. By analyzing key delivery attributes such as delivery time, order arrival time range, compensation policies for delivery delays, and delivery prices, we offer valuable insights into consumer behavior. These insights will, in turn, inform the formulation of effective strategies within the online shopping industry. We examine the following aspects: (a) The willingness of consumers to pay for the service attributes; (b) The relative importance assigned to these attributes by consumers; and (c) The relationship between consumer preferences and socioeconomic characteristics. Using Multinomial Logit Models and a database from a Discrete Choice Experiment, we have discovered that the most significant attributes of delivery service are the time until product arrival and the existence of compensation in case of delivery delays. Additionally, we found that consumers are willing to pay more for the same delivery service if the product is large, as large products generally have higher prices. Furthermore, we observed that delivery time preferences vary by gender and for small products, and price sensitivity varies according to educational level, household size, and socioeconomic status. To the best of our knowledge, no previous research of this kind has been conducted for Chile.

Magnetic resonance image-guided adaptive radiotherapy enables safe CTV-to-PTV margin reduction in prostate cancer: a cine MRI motion study.

We aimed to establish if stereotactic body radiotherapy to the prostate can be delivered safely using reduced clinical target volume (CTV) to planning target volume (PTV) margins on the 1.5T MR-Linac (MRL) (Elekta, Stockholm, Sweden), in the absence of gating. Cine images taken in 3 orthogonal planes during the delivery of prostate SBRT with 36.25 Gray (Gy) in 5 fractions on the MRL were analysed. Using the data from 20 patients, the percentage of radiotherapy (RT) delivery time where the prostate position moved beyond 1, 2, 3, 4 and 5 mm in the left-right (LR), superior-inferior (SI), anterior-posterior (AP) and any direction was calculated. The prostate moved less than 3 mm in any direction for 90% of the monitoring period in 95% of patients. On a per-fraction basis, 93% of fractions displayed motion in all directions within 3 mm for 90% of the fraction delivery time. Recurring motion patterns were observed showing that the prostate moved with shallow drift (most common), transient excursions and persistent excursions during treatment. A 3 mm CTV-PTV margin is safe to use for the treatment of 5 fraction prostate SBRT on the MRL, without gating. In the context of gating this work suggests that treatment time will not be extensively lengthened when an appropriate gating window is applied.

Common due window assignment and single machine scheduling with delivery time, resource allocation, and job-dependent learning effect

Common due window assignment and single machine scheduling with delivery time, resource allocation, and job-dependent learning effect

A REVIEW OF BLOCKCHAIN TECHNOLOGY'S IMPACT ON MODERN SUPPLY CHAIN MANAGEMENT IN THE AUTOMOTIVE INDUSTRY

Blockchain technology has emerged as a transformative force in various industries, including supply chain management within the automotive sector. This review examines the impact of blockchain on the automotive supply chain by analyzing 183 articles, focusing on its ability to enhance transparency, traceability, and efficiency. By providing a decentralized and immutable ledger, blockchain ensures real-time tracking of parts and components, thereby reducing the risk of counterfeit products and ensuring compliance with regulatory standards. The automation of transactions through smart contracts streamlines processes, reduces the need for intermediaries, and leads to substantial cost savings and faster delivery times. However, the implementation of blockchain also presents challenges such as scalability, interoperability with existing systems, high costs, and regulatory concerns. Addressing these challenges through future research and pilot projects is essential for unlocking the full potential of blockchain technology in revolutionizing supply chain management in the automotive industry. This review synthesizes current literature to provide a comprehensive understanding of both the benefits and challenges associated with blockchain implementation, highlighting its transformative potential and the necessary steps for successful adoption.

Implementation of an Automated Code Checking Algorithm Based on Site Analysis

To date, BIM has been primarily utilized in cost and schedule management, an interference check between architectural and structural models and systems based on geometric data in the process of the construction life cycle. However, there is a lack of research that utilizes the information contained in the BIM model to review whether the proposed architectural model is appropriately designed in accordance with each country’s building regulations or building codes or that proposes a model optimized for laws and standards. ‘Building code checking’ is the step of reviewing whether a building designed based on the building codes is suitable for being constructed as a building. However, this process consumes significant time and money and leads to human errors due to the manual review process. This study included implementation of an algorithm based on the Korean building code. In this study, there was the process of selection of codes when architects interpret building codes in common and implementation based on the codes selected. Next, modeling based on DXF files from NGII (National Geographic Information Institute) was applied to the algorithm developed in this study. Last, it includes case studies that compare the outputs of the algorithm with the real buildings, which had received real code checking, to make sure the algorithm in this paper is working properly. The implementation of such an automated system has the potential to significantly improve the efficiency and effectiveness of the building design and construction process. It can help architects to quickly and accurately identify potential legal issues and provide alternative solutions that meet regulatory requirements. This, in turn, can lead to reduced project costs, improved quality of designs, and faster project delivery times.

A scattering-foil free electron beam to increase dose rate for total skin electron therapy (TSET).

Electron beams are used at extended distances ranging between 300 to 700cm to uniformly cover the entirety of the patient's skin for total skin electron therapy (TSET). Even with electron beams utilizing the high dose rate total skin electron (HDTSe) mode from the Varian 23iX or TrueBeam accelerators, the dose rate is only 2500 cGy/min at source-to-surface distance (SSD)=100cm. At extended distances, the decrease in dose rate leads to long beam delivery times that can limit or even prevent the use of the treatment for patients who, in their weakened condition, may be unable to stand on their own for extended periods of time. Previously, to increase dose rate, a customized 6 MeV electron beam was created by removing the x-ray target, flattening filter, beam monitor chamber, and so forth. from the beam path (Chen, et at IJROBP 59, 2004) for TSET. Using this scattering-foil free (SFF) electron beam requires the treatment distance be extended to 700cm to achieve dose uniformity from the single beam. This room size requirement has limited the widespread use of the 6 MeV-SFF beam. This study explores an application of a dual-field technique with a 6 MeV-SFF beam to provide broad and uniform electron fields to reduce the treatment distances in order to overcome treatment room size limitations. The EGSnrc system was used to generate incident beams. Gantry angles between 6 MeV-SFF dual-fields were optimized to achieve the similar patient skin dose distribution resulting from a standard 6 MeV-HDTSe dual-field configuration. The patient skin dose comparisons were performed based on the patient treatment setup geometries using dose-volume-histograms. Similar dose coverage can be achieved between 6 MeV-SFF and 6 MeV-HDTSe beams by reducing gantry angles between dual-field geometries by 8° and 7° at treatment distances of 400 and 500cm, respectively. To achieve 95% mean dose to the first 5mm of skin depth in the torso area, the mean dose to depths of 5-10mm and 10-15mm below the skin surface was 74% (74%) and 49% (50%) of the prescribed dose when using 6 MeV-SFF (6 MeV-HDTSe) beam, respectively. The 6 MeV-SFF electron beam is feasible to provide similar TSET skin dose coverage at SSD ≥ 400cm using a dual-field technique. The dose rate of the 6 MeV-SFF beam is about 4 times that of current available 6 MeV-HDTSe beams at treatment distances of 400-500cm, which significantly shortens the treatment beam-on time and makes TSET available to patients in weakened conditions.