Setup Cost Research Articles

An Optimal Two-Dimensional Maintenance Policy for Self-Service Systems with Multi-Task Demands and Subject to Competing Sudden and Deterioration-Induced Failures

Self-service systems, such as electric vehicle charging piles (EVCPs), are typically deployed without on-site personnel. While frequent maintenance ensures high service revenue, it also leads to significant maintenance setup costs. Therefore, balancing service revenue and maintenance costs is essential for profit maximization. In this paper, we develop a maintenance policy optimization framework to maximize the profit rate of a fleet of self-service systems. First, we propose a maintenance policy that ensures sufficient functional systems while preventing high corrective maintenance costs. Next, we model the fleet's state transition process and its profit rate by characterizing two unique failure-induced demand-and-system interactions: demand switching and stepwise demand arrival rates, where the demands involve multiple tasks and systems are subject to multiple failure modes with non-constant occurrence rates. We develop a Tabu-search algorithm with random exploration to optimize the maintenance policy. Building on this, we investigate the impacts of key model parameters through a case study of thirteen EVCPs in Hong Kong and draw implications for profit maximization.

Seq-Scope: repurposing Illumina sequencing flow cells for high-resolution spatial transcriptomics.

Spatial transcriptomics technologies aim to advance gene expression studies by profiling the entire transcriptome with intact spatial information from a single histological slide. However, the application of spatial transcriptomics is limited by low resolution, limited transcript coverage, complex procedures, poor scalability and high costs of initial setup and/or individual experiments. Seq-Scope repurposes the Illumina sequencing platform for high-resolution, high-content spatial transcriptome analysis, overcoming these limitations. It offers submicrometer resolution, high capture efficiency, rapid turnaround time and precise annotation of histopathology at a much lower cost than commercial alternatives. This protocol details the implementation of Seq-Scope with an Illumina NovaSeq 6000 sequencing flow cell, allowing the profiling of multiple tissue sections in an area of 7 mm × 7 mm or larger. We describe the preparation of a fresh-frozen tissue section for both histological imaging and sequencing library preparation and provide a streamlined computational pipeline with comprehensive instructions to integrate histological and transcriptomic data for high-resolution spatial analysis. This includes the use of conventional software tools for single-cell and spatial analysis, as well as our recently developed segmentation-free method for analyzing spatial data at submicrometer resolution. Aside from array production and sequencing, which can be done in batches, tissue processing, library preparation and running the computational pipeline can be completed within 3 days by researchers with experience in molecular biology, histology and basic Unix skills. Given its adaptability across various biological tissues, Seq-Scope establishes itself as an invaluable tool for researchers in molecular biology and histology.

Multichannel Healthcare: Impact of Asynchronous Telemedicine Adoption on Patient Flow

Problem definition: This paper studies a multichannel healthcare system where physicians diagnose patients and prescribe treatment in-person or through asynchronous telemedicine (AT), a widely adopted yet relatively under-explored form of telemedicine. In collaboration with physicians at the Veterans Healthcare Administration (VHA), we examine the impact of introducing an AT channel on the existing in-person channel and on overall system performance. Methodology/results: VHA implemented AT at select clinics in the state of Georgia in 2012. Using a difference-in-differences design, we find that the introduction of the AT channel led to a sorting process whereby more complex patients were seen in the in-person channel. AT implementation led to a 20% increase in recommended visit time and an 8.5% increase in required clinical resources for in-person consultations. In addition, the adoption of AT resulted in higher throughput—more patients seen by the specialists per month across both channels. Using a fixed-effects model we find a reduction in average wait time for in-person referrals (37.5%), and for the most common medically necessary procedure (43%) despite an increase in the total number of consultations at the specialist clinic. We attribute the improved efficiency to early patient triage, better match between patient needs and treatment modality, and reduction of setup and switching costs in physicians’ workflow. Managerial implications: This paper contributes to our understanding of a rapidly expanding form of healthcare delivery: multichannel healthcare with in-person and AT channels. Our results suggest that healthcare managers and physicians can adopt AT to improve overall system efficiency. At the same time, they should take into account the additional impact of AT on the in-person channel when making capacity decisions and developing guidance on patient referrals. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0235 .

On the Suitability of Process Mining for Enhancing Transparency of Blockchain Applications

AbstractBlockchain technology is known for its transparency properties due to its publicly available, immutable data. Yet, as data availability does not inherently ensure transparency, further analytical methods may be required for human interpretation of data traces. Process mining has emerged as a popular toolbox for understanding processes and how they are executed in practice. The paper studies process mining as a method to enhance the transparency of blockchain data. To this end, two popular Ethereum applications were analyzed using process mining: the prediction and betting marketplace Augur and the network marketing platform Forsage. Observations from the process-mining analyses are used to discuss if process mining can serve as a method to establish transparency of a blockchain. For both applications, new insights are generated for usage scenarios such as application redesign, security analysis, user behavior analysis, and revealing blind spots in Augur’s and Forsage’s documentation. The paper concludes that there is evidence that process mining can serve as a method to enhance transparency in blockchains at the cost of technical setup and knowledge acquisition.

Enhancing Surveillance Systems with Cost-Effective Ultrasonic Radar for Object Detection and Tracking

Object detection is critical in surveillance systems because it enables timely identification of unauthorized objects, which is essential for maintaining security and mitigating risks. Existing approaches to surveillance typically suffer from limited coverage, variable detection range, moderate accuracy, high cost, and complex setup requirements. This article presents an approach to object detection using microcontroller-based ultrasonic sensors. Our approach leverages four distinct processing phases to create a radar-like system capable of real-time detection and autonomous decision-making. In this study, we conducted experiments by integrating more than six peripheral modules with the Arduino platform. By evaluating 17 diverse test cases in various scenarios and environments, the approach demonstrated enhanced object tracking and robustness compared to existing methods. The system effectively detects objects within the targeted area, providing precise distance measurements (around 50 cm) and position information (0 to 360 degrees). Moreover, our approach enabled the identification of three risk zones—medium, high-risk, and mild danger—within the critical region, contributing to improved security and risk management. The results reveal the system’s effectiveness in real-time detection, accurate distance estimation, and comprehensive risk assessment. Overall, our study significantly contributes to the advancement of object detection technology by effectively addressing the limitations of existing methods and offering a cost-effective and practical solution. Our research has the potential to monitor objects in surveillance systems across various domains, with significant implications for enhancing security, risk mitigation, and monitoring in industries reliant on effective object detection systems. Jagannath University Journal of Science, Volume 11, Number 1, June 2024, pp. 157−171

The quadratic knapsack problem with setup

The Quadratic Knapsack Problem is a well-known generalization of the classical 0-1 knapsack problem, in which any pair of items produces a pairwise profit if both are selected. Another relevant generalization of the knapsack problem is the Knapsack Problem with Setup, in which the items are partitioned into classes, the items of a class can only be inserted into the knapsack if the corresponding class is activated, and activating a class involves a setup cost and a setup capacity reduction.Despite a rich literature on these two problems, their obvious generalization, i.e., the Quadratic Knapsack Problem with Setup, was never investigated so far. We discuss applications, mathematical models, deterministic matheuristic algorithms, and computationally evaluate their performance.

A Comprehensive Overview on Sustainable Vegetable Gardening: Eco-friendly Approaches to Home Grown Production

Sustainable vegetable gardening is an eco-friendly practice that integrates organic farming principles, resource conservation, and biodiversity promotion to produce nutritious, chemical-free food while minimizing environmental impact. This approach emphasizes soil health through the use of organic amendments, crop rotation, composting, and mulching to improve fertility and water retention. Water conservation techniques, such as drip irrigation and rainwater harvesting, are employed to optimize water use, especially in arid regions. Pest and disease management relies on integrated pest management (IPM), biological controls, companion planting, and the use of organic pesticides to reduce chemical input while maintaining crop health. Sustainable homegrown produce has been shown to have superior nutritional content compared to commercially grown produce, and the avoidance of synthetic chemicals reduces the risk of pesticide residue exposure. Gardening fosters healthy eating habits by connecting individuals to their food sources, encouraging the consumption of fresh, unprocessed vegetables, and contributing to food security. The mental and physical health benefits of gardening, including reduced stress, increased physical activity, and improved mental well-being, further highlight its holistic value. However, challenges such as the initial setup costs, time investment, pest management, and knowledge gaps can hinder widespread adoption. Addressing these challenges requires greater access to resources, educational initiatives, and the development of climate-resilient practices tailored to specific regions. Future trends in sustainable gardening include the adoption of technological innovations, such as smart irrigation systems, automation, and vertical farming, which offer scalable solutions for urban and small-scale gardeners. The COVID-19 pandemic has underscored the importance of resilient, local food systems, and sustainable gardening is poised to play a critical role in addressing future food security concerns.

Live streaming channel and product assortment with both national and store brand products

To counteract the fierce competition in the online retailing market, retailers are increasingly adopting live streaming selling model and introducing store brand product to enhance their competitiveness. In this context, we attempt to examine whether and when a retailer should launch a live streaming channel. If launched, we further investigate how the retailer should assort both national and store brand products across available channels. To delve into these questions, we consider a supply chain consisting of a manufacturer and an online retailer, where the retailer resells the manufacturer's national brand product and also sells a store brand product. We examine the retailer's optimal channel strategy and product assortment strategy by considering six scenarios, differentiated by whether introducing the live streaming channel and various product assortment tactics. Our findings indicate that as long as the fixed setup cost of the live channel is relatively low, the retailer will always introduce a live streaming channel. The retailer's optimal assortment of both products across channels highly depends on the consumers’ additional value derived from the live streaming channel and the perceived quality of the store brand product. We also find that, the retailer's optimal channel strategy and product assortment may not always benefit the manufacturer, but there exist conditions that can create win-win situations for both players. Our study further shows that if the retailer launches the live streaming channel at the start, it may not always be necessary to introduce the store brand product under certain conditions.

Opportunistic maintenance for a novel load-sharing system with dependent degradation rate and volatility

For traditional degrading load-sharing systems, a typical assumption lies in the only effect of unit load on its degradation rate. However, motivated by a laser system example with positive correlation between degradation rate and volatility, we present a novel load-sharing system with general degradation rate-volatility-load correlation. Furthermore, to take account for unit economic dependence caused by sharable maintenance set-up cost, and the window period generated by the maintenance on some unit, opportunistic maintenance (OM) strategy is introduced to offer the opportunity of simultaneously maintaining another working unit under control-limit criteria. Based on the semi-regenerative process, the long-run average cost rate is minimized to obtain the optimal inspection interval, preventive maintenance and OM thresholds. Compared to the traditional condition-based maintenance strategy separately for each unit, the effectiveness of OM strategy is validated through numerical examples and case studies, offering broad managerial insights for engineers to reduce maintenance expenses.

Material and Parametric Design Optimization of Improved Heat Transfer Rate of AC Condenser

Air conditioner system is made up of a condenser that removes unwanted heat in an enclosure through the refrigerant and transfers the heat outside. Improving the heat transfer of air conditioning condenser is still a difficult task because of the broader set of materials and various parametric designs involved. Due to this high cost, the experimental set-up cost cannot be modified, instead, simulation analysis was introduced in the optimization process in order to achieve a near-optimal solution. The aim of this research is to improve the heat transfer rate for air conditioning condenser by material and parametric design optimization. The system was designed based on one basic parameter optimization: varying the condenser tube diameter. This variable was changed in order to improve the heat transfer of the condenser. Simulations using Computational Fluid Dynamic (CFD) analysis and thermal analysis were carried out to have a better understanding and distinct visualization of the fluid flow and materials used, and to compare the results. The materials that were used for CFD analysis are R32 and R290, and for thermal analysis are copper (C12200) and aluminum. The analysis was done using Analysis System (ANSYS) software. Different parameters were calculated from the results that were obtained and graphs were plotted between various parameters such as heat flux, static pressure, velocity, mass flow rate and total heat transfer. From the CFD analysis, the result shows that R32 has more static pressure, velocity, mass flow rate and total heat transfer than R290 at a condenser tube diameter of 7mm. In thermal analysis, the heat flux is more for copper (C12200) material at a condenser tube diameter of 7mm than aluminum.

Optimasi Ukuran Lot Persediaan dalam Model Integrasi Single Vendor dan Single Buyer dengan Mempertimbangkan Kekurangan Buyer

<p><strong>The supply chain is the main factor influencing the production process in achieving goals. This research develops a model to determine the optimal production lot size in the supply chain system between vendors and buyers by considering the inventory shortage at the buyer. Minimizing the combined inventory cost is the goal of optimizing the production lot size by developing an integration model to determine the optimal lot size. The proposed model uses a periodic delivery method from the vendor to the buyer and allows for inventory shortages at the buyer. An iterative algorithm is applied to find the optimal lot size and minimum integrated inventory cost. The results showed that the initial model with n=1 resulted in a total cost of 2252 and an optimal production size (Q*) of 457. The proposed model reduces the total cost to 1605 with an optimal production size (Q*) of 737. Sensitivity analysis showed that an increase in the frequency of deliveries to vendors and vendor set-up costs contributed to a rise in total cost, while an increase in vendor storage costs led to a decrease in production lot size. This research can improve the efficiency of production planning and inventory management in the supply chain.</strong></p><p><strong><em>Keywords</em></strong> - <em>Inventory, Shortages, Single Buyer</em><em>, Single Vendor.</em></p>

Applications of capillary electrophoresis with capacitively coupled contactless conductivity detector (CE-C4D) for the determination of glucosamine, vitamin B6 and minerals

Capillary electrophoresis with capacitively coupled contactless conductivity detector (CE-C4D) is renowned for its numerous advantages, such as compact equipment, low cost of setup and operation, simplicity in functionality, and minimal use of samples and chemical solvents. This method has been applied across various fields, including environmental analysis, forensic science, biochemistry, pharmaceuticals, and food science. In this study, the CE-C4D method was applied to determine the presence of glucosamine, vitamin B6, and certain minerals in dietary supplements. Notably, glucosamine was simultaneously determined with calcium, and vitamin B6 with magnesium. The method was validated to meet the requirements of AOAC. The detection limits achieved for calcium, glucosamine, vitamin B6 and magnesium were 0.05 ppm; 0.50 ppm; 0.10 ppm and 1.00 ppm, respectively. The concurrent determination of active substances with different properties within a single product is crucial, optimizing analytical efficiency and yielding high accuracy for the analysis.

A MATLAB platform for production planning in batch processing firms producing items that are jointly replenished

Rising levels of poverty have prompted manufacturers of non-durable consumer goods to explore opportunities at the lower end of the wealth spectrum. To enhance affordability for low-income consumers, these goods are often packaged in various sizes, including single-serve sachets. While numerous models and algorithms have been developed to determine the optimal frequency of manufacturing runs and packaging setups for the simultaneous replenishment of different pack sizes, there is a notable lack of literature addressing their implementation by small and medium-sized enterprises (SMEs) in this sector. This gap may be attributed to the absence of accessible source codes, a shortage of model experts, and the complexity involved in manual calculations. To address this issue, we developed a user-friendly MATLAB software platform based on Goyal’s algorithm, tailored specifically for SMEs. The software prioritizes simplicity, interactivity, and flexible visual displays. It was validated against examples from existing literature and through randomly generated scenarios. Users can easily compute the optimal number of manufacturing setups, packaging frequencies for each pack size, and the associated costs by inputting relevant data such as manufacturing setup, inventory holding and packaging setup costs, and demand for each pack size. Importantly, users do not need expertise in modeling to operate the software. However, it is designed for single-product deterministic environments; future research should explore multi-product and stochastic modeling scenarios.

An open-source combined atomic force microscope and optical microscope for mechanobiology studies

Atomic Force Microscopy (AFM) has become the gold standard tool for measuring mechanical properties of biological samples including proteins, single cells and tissues. However, investment in this specialized equipment and gaining expertise in its operation are significant obstacles for non-experts looking to adopt this technique. To address this, we have designed an AFM based mechanical measurement system for measuring cell mechanical properties which is combined with a custom inverted fluorescence microscope which can be used for characterizing mechanosensitive responses. This system, through its ease of use and low setup cost, will promote interdisciplinary research leading to new insights into the role of cell mechanics and mechanosensitive responses in physiology and disease.

A waste reduction strategy through autonomation under a closed-loop supply chain management

Currently, apart from manufacturing processes, the remanufacturing of products is considerably important. Appropriate remanufacturing requires the operation of long-run manufacturing systems. However, in long-run processes, the production system may convert to an out-of-control state due to machine breakdowns. Then, defective products are frequently produced; this increases wastage and disrupts environmental sustainability. In this model, a smart autonomation policy is deliberated for an error-free inspection in separating defective products during production. The autonomation policy facilitates waste reduction through remanufacturing. This paper concentrates on customer awareness and service-dependent demand, which directly improves the overall profitability of the system. A discrete investment to reduce setup cost, continuous investment to collect used goods, and cap-and-trade strategy to limit carbon emission are considered to obtain a more realistic model. Classical optimization method is applied for global maximum profit test of the profit function with respect to cycle length, customer awareness, service investment, discrete investment to reduce setup cost, number of shipments, and container capacities. Numerical testing, sensitivity to total profit in different cost parameters, and comparisons with previous research are explained. Some special scenarios including graphical representations are discussed to prove that a large investment is more beneficial than the cost of specific setup and collection.

An 'alcohol health champions' intervention to reduce alcohol harm in local communities: a mixed-methods evaluation of a natural experiment.

Globally alcohol consumption is a leading risk factor for premature death and disability and is associated with crime, social and economic consequences. Local communities may be able to play a role in addressing alcohol-related issues in their area. To evaluate the effectiveness and cost-benefit of an asset-based community development approach to reducing alcohol-related harm and understand the context and factors that enable or hinder its implementation. A mixed-methods evaluation. Area-level quasi-experimental trial analysed using four different evaluation methods (a stepped-wedge design where each area was a control until it entered the intervention, comparison to matched local/national controls and comparison to synthetic controls), alongside process and economic evaluations. Ten local authorities in Greater Manchester, England. The outcomes evaluation was analysed at an area level. Ninety-three lay persons representing nineareas completed questionnaires, with 12 follow-up interviews in five areas; 20 stakeholders representing ten areas were interviewed at baseline, with 17 follow-up interviews in eight areas and 26 members of the public from two areas attended focus groups. Professionals in a co-ordinator role recruited and supported lay volunteers who were trained to become alcohol health champions. The champion's role was to provide informal, brief alcohol advice to the local population and take action to strengthen restrictions on alcohol availability. Numbers of alcohol-related hospital admissions, accident and emergency attendances, ambulance call-outs, street-level crime and antisocial behaviour in the intervention areas (area size: 1600-5500 residents). Set-up and running costs were collected alongside process evaluation data exploring barriers and facilitators. Routinely collected quantitative data on outcome measures aggregated at the intervention area and matched control and synthetic control areas. Data from policy documents, licensing registers, meeting notes, invoices, time/cost diaries, training registers, questionnaires, interviews, reflective diaries and focus groups. The intervention rolled out in nine out of ten areas, seven of which ran for a full 12 months. Areas with better-established infrastructure at baseline were able to train more champions. In total, 123 alcohol health champions were trained (95 lay volunteers and 28 professionals): lay volunteers self-reported positive impact. Champions engaged in brief advice conversations more readily than taking action on alcohol availability. There were no consistent differences in the health and crime area-level indicators between intervention areas and controls, as confirmed by using three different analysis methods for evaluating natural experiments. The intervention was not found to be cost-beneficial. Although the sequential roll-out order of the intervention was randomised, the selection of the intervention areas was not. Self-reported impact may have been subject to social desirability bias due to the project's high profile. There was no measurable impact on health and crime outcomes. Possible explanations include too few volunteers trained, volunteers being unwilling to get involved in licensing decisions, or that the intervention has no direct impact on the selected outcomes. Future similar interventions should use a coproduced community outcomes framework. Other natural experiment evaluations should use methodological triangulation to strengthen inferences about effectiveness. This trial is registered as ISRCTN81942890. This award was funded by the National Institute for Health and Care Research (NIHR) Public Health Research programme (NIHR award ref: 15/129/03) and is published in full in Public Health Research; Vol. 12, No. 9. See the NIHR Funding and Awards website for further award information.

Syneresis-Driven Self-Refilling Printing of Geometry/Component-Controlled Nano/Microstructures.

Nano/microfabrication is of fundamental importance both in scientific and industrial situations. There are, therefore, many attempts at realizing easier, quicker, and more precise fabrication of various structures; however, achieving this aim without a bulky and costly setup is still challenging. Here, we introduce a facile and versatile means of printing an ordered structure consisting of nanoscale stripes and more complicated geometries including pillars and wavy form with a lateral resolution of single micrometers. To this end, we prepare a polydimethylsiloxane (PDMS) slab with an oxygen plasma-induced wrinkled surface where liquid PDMS exudes by syneresis. Since this liquid PDMS is automatically loaded, the printing is repeatable without inking. A substrate moderately wettable to the liquid PDMS as well as amount/property-controlled syneresis is primarily important for the creation of well-defined structures. Precisely controlling these conditions will make this method universally applicable to diverse substrates and liquids including suspensions.

Asymptotically optimal energy consumption and inventory control in a make-to-stock manufacturing system

We study a make-to-stock manufacturing system in which a single server makes the production. The server consumes energy, and its power consumption depends on the server state: a busy server consumes more power than an idle server, and an idle server consumes more power than a turned-off server. When a server is turned on, it completes a costly set-up process that lasts a while. We jointly control the finished goods inventory and the server’s energy consumption. The objective is to minimize the long-run average inventory holding, backorder, and energy consumption costs by deciding when to produce, when to idle or turn off the server, and when to turn on a turned-off server. Because the exact analysis of the problem is challenging, we consider the asymptotic regime in which the server is in the conventional heavy-traffic regime. We formulate a Brownian control problem (BCP) with impulse and singular controls. In the BCP, the impulse control appears due to server shutdowns, and the singular control appears due to server idling. Depending on the system parameters, the optimal BCP solution is either a control-band or barrier policy. We propose a simple heuristic control policy from the optimal BCP solution that can easily be implemented in the original (non-asymptotic) system. Furthermore, we prove the asymptotic optimality of the proposed control policy in a Markovian setting. Finally, we show that our proposed policy performs close to optimal in numerical experiments.

Reducing operational costs in a manufacturing system that incorporates quality assurances, probabilistic failures, overtime and outsourcing

This research focuses on the dynamic landscape of today's competitive market, where production management must meet clients' expectations for high-quality products and shorter lead times while managing internal disruptions due to inevitable defects and unpredictable equipment failures. Achieving these operational goals without compromising product quality, missing deadlines, or experiencing production disruptions is essential for minimizing operational expenses. The study examines the dynamics of the system's operating costs through the development of models, mathematical formulations, optimization techniques, and algorithm proposals. It demonstrates the system's convexity and establishes the optimal batch time for implementing the proposed methodologies. The research results show relevant failure costs of 3.51 %, overtime added costs of 4.57 %, outsourcing setup costs of 0.73 %, outsourcing variable costs of 41.82 %, quality-related costs of 2.98 %, in-house variable costs of 40.42 %, and in-house holding costs of 3.55 %. The study develops strategies for optimal overtime use to meet production targets without excessive labor costs and provides a structured framework for making informed outsourcing decisions that balance cost savings with quality and reliability considerations. Overall, the research provides a robust framework for reducing operational costs while maintaining or improving the quality and reliability of manufacturing processes

SISTEME VERTICALE HIDROPONICE: INTENSIFICAREA REZISTENȚEI LA CLIMĂ, EFICIENȚEI APEI ȘI AGRICULTURII URBANE

This paper explores hydroponic vertical systems as a sustainable solution to modern agricultural challenges, particularly those posed by climate change. Hydroponics, a method of growing plants without soil using nutrient-rich water solutions, offers significant advantages over traditional farming. Vertical systems maximize space efficiency by growing plants in stacked layers, making them ideal for urban environments with limited space. These systems provide a controlled environment that mitigates the impacts of extreme weather, ensuring consistent crop production. The paper reviews various hydroponic techniques, including deep water culture, nutrient film technique, flood and drain, and drip irrigation. It highlights the efficiency of water use in hydroponics, crucial for areas facing water scarcity. Advanced technologies, such as sensors, automated nutrient delivery, and LED lighting, are employed to optimize growing conditions, enhance resource use efficiency, and improve crop yields. LED lights, in particular, offer energy efficiency, customizable spectra, and low heat output. Mathematical models are used to maximize plant development and resource efficiency, providing a framework for understanding plant-environment interactions. Despite high initial setup costs and the need for technical expertise, hydroponic systems present long-term economic and environmental benefits. This paper underscores hydroponic vertical systems' potential to revolutionize urban agriculture, ensuring food security and sustainability amidst climate change challenges.