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In this paper, we study the implications of extending the balanced cost reduction property from queueing problems to general games. As a direct translation of the balanced cost reduction property, the axiom of balanced externalities for solutions of games, requires that the payoff of any player is equal to the total externality she inflicts on the other players with her presence. We show that this axiom and efficiency together characterize the Shapley value for 2-additive games. However, extending this axiom in a straightfoward way to general games is incompatible with efficiency. Keeping as close as possible to the idea behind balanced externalities, we weaken this axiom by requiring that every player's payoff is the same fraction of its total externality inflicted on the other players. This weakening, which we call weak balanced externalities, turns out to be compatible with efficiency. More speci fically, the unique efficient solution that satisfi es this weaker property is the proportional allocation of nonseparable contribution (PANSC) value, which allocates the total worth proportional to the separable costs of the players. We also provide characterizations of the PANSC value using a reduced game consistency axiom.

The article studies Automatic Oil Spraying Machine design and manufacture for baking device. In a current baking process, the workers manually spray the oil onto the trays. The spraying cycle increases the cost of man power in small scale industries. An automated oil spraying system is designed to solve these issues, where they can automatically spray the oil on the baking tray easily and effectively. The main components of this device are the mechanical and electrical components. The mechanical portion consists of conveyor belt, roller, bearing, gear, nozzle and tank, and mechanical structure. The electrical components include the IR sensor module, the dc motor, the dc pump, Arduino, and the source of the batteries. The key advantages of this approach are high precision oil spraying; improve efficiency, cost reduction and manpower. This model system's gross weight contains 15 kg (roughly). The efficiency of this device is checked for product production under different working conditions to track the performance of the work and the time durations.

Magnesium (Mg) alloys are extensively used in the automotive and aircraft industries due to their prominent properties. The selection of appropriate process parameters is an important decision to be made because of the cost reduction and quality improvement. This decision entails the selection of suitable process parameters concerning various conflicting factors, so it has to be addressed with the Multiple Criteria Decision Making (MCDM) method. Therefore, this work addresses the MCDM problem through the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and COPRAS (COmplex PRoportional ASsessment) methods. The assessment carried out in the material Mg AZ91 with the Solid Carbide (SC) drill bit. The dependent parameters like drilling time, burr height, burr thickness, and roughness are considered with the independent parameters like spindle speed and feed rate. Drilling alternatives are ranked using the above said two methods and the results are evaluated. The optimum combination was found on the basis of TOPSIS and COPRAS for simultaneous minimization of all the responses which is found with a spindle speed of 4540 rpm and a feed rate of 0.076 mm/rev. The identical sequencing order was observed in TOPSIS and COPRAS method. The empirical model was developed through Box-Behnken design for each response. Superior empirical model developed for drilling time which is 3.959 times accurate than the conventional equation. The trends of various dependents based on the heterogeneity of various independents are not identical, these complex mechanisms are identified and reported. The optimized results of the Desirability Function Approach are greater accordance with the TOPSIS and COPRAS top rank. The confirmation results are observed with lesser deviation suggesting the selection of the above independent parameters.

Suppliers often impose a minimum order quantity (MOQ) to ensure that production runs and shipping quantities of each specific item are economically viable. Additional economies of scale may arise as various items share high joint costs (e.g. the cost of an overseas container shipment) and require coordination of their replenishment policies. The buyer needs to find the joint ordering interval and replenishment policies for each of the individual items to minimize the system-wide ordering and inventory costs while satisfying the quantity restrictions. We focus on the case of constant demand without backlogging. Given a fixed joint reorder interval, we characterize the optimal inventory ordering strategy for each item, which we refer to as Multi-Replenishment (MR) inventory ordering policy, and derive a closed-form expression for the optimal average inventory costs per unit of time. In contrast to the previous literature, the MR inventory ordering policy does not follow the zero-inventory-ordering (ZIO) rule and allows for orders of different sizes over time to optimally accommodate the MOQ restriction. A numerical approach is used to determine the optimal joint reorder interval, and is later extended to account for the presence of empty replenishments. An extensive computational study shows 1) the total inventory and setup cost reduction associated with the MR inventory policies and empty replenishments; 2) the impact of various parameters on cost and policy performance; and 3) the loss associated with discretizing time at different levels of granularity (weeks, days, hours, minutes, seconds) to accommodate restrictions in the timing of item deliveries.

In this paper, bulk water abstractions and a purification process in terms of water pumped energy consumption, is modelled and simulated. The study proposes an optimal energy consumption-rate management system, using real-time data. The aim is to achieve the goal of obtaining potable water by scheduling the pumping process, to obtain the cheapest energy-rate at any given load demand. Considering the loss due to the effect of evaporation, the effect of precipitation (or rainfall) and seepage losses. As a baseline, an electronic timer switching system for the powering of electrical pumps, used to pump water from one level to another, is incorporated. An optimal control system is included that looks at the energy cost before scheduling the pumping sequence in such a way that pumping occurs during the more affordable energy costing period and ensures that the water demand from consumers matches the water pump level in the storage reservoir. The configuration involved the time of use (TOU) tariff; in the context of the South African electricity tariff. The optimal control output, compared to an electronic timer switching system, shows an end-of-day cost reduction of 1994 ZAR in water-pumped energy consumption from the grid. This reduction in energy consumption is therefore a direct reflection of the reduction in the cost of water supply to consumers.

Automated driving technology is one of the emerging technologies which will change the transportation mode in the future. Distributing the automated driving vehicles from the automobile factory to dealers has a huge difference compared with traditional vehicles. This paper considers the variety of cases where the automated driving vehicles can be both distribution tools and distribution goods. Then establishes a new distribution model that integrates self-distribution of autonomous vehicles into the existing distribution rings form a complex network composed of ring-branches. This cooperative distribution model of automated driving and traditional vehicle transport to minimize transportation cost and maximize the overall efficiency. Furthermore, we design an improved adaptive large neighborhood algorithm (ALNS) to solve the model which combines the merger heuristics and splitter heuristics to promote generate the optimal solutions. The efficiency of our proposed method is proved by real-world data from an automobile enterprise. Additionally, the sensitivity analysis of the maximum distance for automated driving vehicles to be delivered by themselves suggests that the larger distance, the more outstanding of cost reduction and efficiency increase for our proposed model.

Improving the performance and the production of renewable energy sources, especially the wind energy, is considered an attractive approach to reduce the Cost of Energy (COE) associated to the hydrogen generation process. In this context, flow control strategies have been object of detailed investigation during last years. Originally flow control devices were designed to be implemented in the aeronautical sector. Nonetheless, the optimization of the performance of the wind turbine blades with the introduction and implementation of these devices is being widely investigated these days. An analysis of the influence of implementing Vortex Generators (VGs) and Gurney Flaps (GFs) in Wind Turbine Blades (WTBs) on the Annual Energy Production (AEP) of large Horizontal Axis Wind Turbine (HAWT) is proposed in this paper. For that purpose, the Weibull distributions of annual wind speed data series of a real wind farm have been calculated, and Blade Element Momentum (BEM) based calculations have been performed to evaluate the effect of the flow control devices on the power curve and the AEP of the NREL offshore 5 MW Baseline Wind Turbine. The obtained results show an enhancement of the AEP of the turbine of 2.43% during year 2015 and 2.68% during year 2016. As a result, increments of the generated hydrogen volume larger than 130000 Nm3 are achieved during both years with no considerable additional cost in the design of the wind turbine.

With continuously decreasing circuit scale, more and more test patterns (test contents) are added to test set to achieve acceptable defect levels, which seriously affect test time and, consequently, test cost. Theoretically, dropping invalid (pattern that can make the test pass) test patterns can reduce test cost. In fact, When the valid (pattern that can make the test fail) and invalid patterns overlap seriously, identifying effective patterns performs poorly, which will not achieve the expected results. This paper proposes a kind of eliminate redundancy method, so that this LDA-MRMR algorithm which can provide test cost reduction without increasing the defect level obviously. Experimental results demonstrate that the proposed method sacrifices 3% of the predictive accuracy in exchange for 3.7 times time saving compared with traditional methods. In addition, the algorithm is completely software-based and does not require any additional hardware overhead and is directly compatible with traditional integrated circuit testing process.

Purpose We aim to assess the healthcare value achieved from a shared savings program for pediatric appendectomy. Methods All appendectomy patients covered by our health plan were included. Quality targets were 15% reduction in time to surgery, length of stay, readmission rate, and patient satisfaction. Quality targets and costs for an appendectomy episode in two 6-month performance periods (PP1, PP2) were compared to baseline. Results 640 patients were included (baseline:317, PP1:167, PP2:156). No quality targets were met in PP1. Two quality targets were met during PP2: readmission rate (−57%) and patient satisfaction. No savings were realized because the cost reduction threshold (−9%) was not met during PP1 (+1.7%) or PP2 (−0.4%). Conclusions Payer-provider partnerships can be a platform for testing value-based reimbursement models. Setting achievable targets, identifying affectable quality metrics, considering case mix index, and allowing sufficient time for interventions to generate cost savings should be considered in future programs.

INTRODUCTION Integrated quality improvement (QI) and cost reduction strategies can help increase value in cancer care. Time-driven activity-based costing (TDABC) is a bottom-up costing tool that measures resource use over the full care cycle. We applied standard QI and TDABC methods to improve workflow efficiency and reduce costs for MRI-guided prostate brachytherapy. METHODS AND MATERIALS We constructed process maps of the baseline prostate brachytherapy workflow from initial consultation through one year after treatment. Process maps reflected resources and time required at each step. TDABC costs were calculated by multiplying each process time by the cost per min of the resource(s) used at that step. We then used plan-do-study-act methodology to identify workflow inefficiencies and implement solutions to reduce resource consumption. RESULTS The highest cost components at baseline were the operating room (OR) (40%), imaging (8.7%), and consultation (7.6%). Higher-than-expected costs (3%) were incurred during surgery scheduling. After targeted QI initiatives, OR time was reduced from 90 to 70 min, which reduced overall cost by 5%. Personnel task downshifting reduced costs by 10% at consultation and 77% at surgery scheduling. Re-engineering of follow-up protocols reduced costs by 8.4%. Costs under the new workflow decreased by 18.2%. CONCLUSIONS TDABC complements traditional QI initiatives by quantifying the highest cost steps and focusing QI initiatives to reduce costs and improve efficiency. As payment reform evolves toward bundled payments, TDABC and QI initiatives will help providers understand, communicate, and improve the value of cancer care.

Reductions in defense expenditure require holistic and coordinated planning of two critical and interconnected defense capabilities, namely a fleet of assets and the workforce required. In this paper, we model and solve a joint problem of strategic workforce planning and fleet renewal in a military context. The joint problem studied involves addressing a trade-off among several costs (e.g., workforce, maintenance, operating, etc.) and operational readiness (availability) of the fleet. To make such trade-offs, the decisions associated with workforce planning (i.e., the recruitment and the career progression of the workforce) and fleet renewal (i.e., the timing of asset replacements) strategies have to be simultaneously considered and optimized. We develop a simulation-optimization approach by coupling a system dynamics (SD) simulation model and a genetic algorithm (GA) to solve the joint problem. In the developed approach, the GA generates candidate workforce planning and fleet renewal strategies to find the best joint strategy. Then, the candidate workforce planning and renewal strategies are passed to the SD model which simulates both the career progression of the workforce and the life-cycle of assets to evaluate the total cost. We illustrate the applicability and effectiveness of the joint model on a realistic case study motivated by the recent modernization efforts of the Royal Australian Navy. The results obtained indicate that this approach leads to a considerable cost reduction and identifies the causes of inferior performance. We also test the robustness of the optimized strategies under uncertainty by sensitivity and scenario discovery analyses to infer further insights.

The Internet of Things (IoT) foresaw a transparent network between the real and virtual worlds. IoT offers a promising potential to develop strong market and industrial applications. The export-oriented economy of industrial manufacturers relies on product and service creativity to retain a competitive advantage. The IoT-based applications of innovative manufacturing companies (IOTs), where most companies are involved and engaged in many of the case IoT-based applications, is motivated by computing capacity, networking, cost reduction and electronic components. A common motive is the Internet of Things applications and the improvement of after-sales service activities. The suggested Linear Product Design Regression (LPDR) algorithm classifies business product innovation design based on consumer input to support business development. Businesses, companies and the technology industry: the inhibitors hinder the development of the four IT applications. IoT offers one of the latest innovations in manufacturing to allow us to meet key challenges. The product design and development engineering are engaged in utilizing the Internet of Things (IoT) to create comprehensive policies and policy creation for manufacturing companies.To support business development. Businesses, companies and the technology industry: the inhibitors hinder the development of the four IT applications. To allow us to meet key challenges and to create comprehensive policies and policy creation for manufacturing companies.

A bstract The use of shared vehicle architectures with BEVs offers a high potential for FCEVs in terms of cost reduction. Therefore, the hydrogen must be stored in the box-shaped design space in the underbody of the vehicles, where the battery in BEVs is located. Box-shaped pressure vessels show the potential to store high amounts of hydrogen in this design space. An optimal design of a type I box-shaped pressure vessel with inner tension struts is investigated in literature. In this study, the relatively low efficiency of this type of pressure vessel is presented first. This motivates to work out the possibilities to increase the efficiency by reducing the total weight. Therefore, a numerical analysis is conducted to reinforce the vessel wall with fiber reinforced composite in the main section of this study. In a first step the possible measures to reinforce the pressure vessel are analyzed and evaluated. Then, a basic design, which serves as a baseline for the numerical studies, is determined analytically. Using a numerical model, the structure of the reinforcement and the acting loads are investigated with finite element method in parametric studies varying several parameters. Based on the knowledge gained, optimal design parameters are derived. These design parameters allow a comparison of the pressure vessel efficiency with other pressure vessel types and enable the evaluation of this vessel concept.

Preventing an increase in emission intensity requires a transition to a renewable-based electricity system. Wind and solar power are often the major contributors to this transition. The inherently variable nature of the generation pattern of these renewable sources impels the inclusion of storage technologies. But how to combine renewable and diverse storage technologies in a cost-competitive way? This paper addresses this question by constructing the first open-sourced, spatially, and hourly resolved model of the Indian power system and analysing the system for cost-optimal storage combinations. Increasing the renewable share targets from 30% to 75% of electricity supply, the levelized costs and storage technology options for various energy scenarios are assessed. Results show that the system cost of electricity can vary between 3.65 R/kWh and 4.37 R/kWh with the help of transmission expansion and inter-regional coordination. 50% of RES penetration is found to be a critical target beyond which the total annual system cost increments rise sharply. The optimal solution at 50% RES share includes a maximum of 11 GWh of battery and 29.8 GWh of hydrogen storage capacity. Sensitivity analysis shows that cost reduction in the storage technologies results in the lowest system cost even with limited transmission expansion.

Brushless DC motors have been widely used in both industrial and non-industrial applications. Commercialization of these drives by reducing their price and increasing reliability, are among the main goals of manufacturers and researchers. These goals have been partially achieved by reducing the number of switches, current or voltage sensors, and elimination of position sensors. However, according to statistics the electrolytic capacitors are both costly and inherently have the highest potential of drive failure. In this study a new control method is proposed based on simultaneous control of speed and torque in order to eliminate the high capacity electrolytic capacitors, and use switching thin-film capacitor with low capacity in DC link instead. This reduces the torque ripples resulting from voltage fluctuations in the DC-link. The validity of the proposed method was demonstrated via simulation. A laboratory prototype of the drive was also implemented to verify the theoretical and simulation results.

A Linear Fresnel Collector (LFC) is a solar concentrating technology with high potential for improvements and therefore significant cost reduction. However, LFC optimization studies found in literature show little agreement regarding optimal geometry. In this article, a study is presented to evaluate the trends of the main geometrical parameters in an optimization process of medium temperature linear Fresnel collectors (LFCs) with trapezoidal receiver. For this, a comprehensive LFC design model was developed. It includes an optical, a thermal, an annual integration of the collected energy and an economic sub-models coded in a hard-link way. This model was used to investigate the influence of the main LFC geometrical parameters and inputs on the levelized cost of heat (LCOH) produced. The geometrical parameters investigated were the number of mirrors, the width of mirrors, the gap between mirrors, the trapezoidal angle and the trapezoidal height of the receiver, while the inputs investigated were the location (Quito-Ecuador and Targassone-France), DNI data (TMY data and clear sky model) and the time frame of simulation (representative days or the whole year). Results show that the optimal LFC geometry depends mainly on the azimuthal movement of the Sun. Consequently, the trends of the energetic behavior of an LFC, when the geometrical parameters vary, are similar without regard of the latitude, DNI data or the time frame used for simulations. Reductions until 20% on the LCOH may be achieved by optimizing the geometry of such LFC.

Plug-in hybrid fuel cell and battery propulsion systems appear promising for decarbonising transportation applications such as road vehicles and coastal ships. However, it is challenging to develop optimal or near-optimal energy management for these systems without exact knowledge of future load profiles. Although efforts have been made to develop strategies in a stochastic environment with discrete state space using Q-learning and Double Q-learning, such tabular reinforcement learning agents’ effectiveness is limited due to the state space resolution. This article aims to develop an improved energy management system using deep reinforcement learning to achieve enhanced cost-saving by extending discrete state parameters to be continuous. The improved energy management system is based upon the Double Deep Q-Network. Real-world collected stochastic load profiles are applied to train the Double Deep Q-Network for a coastal ferry. The results suggest that the Double Deep Q-Network acquired energy management strategy has achieved a further 5.5% cost reduction with a 93.8% decrease in training time, compared to that produced by the Double Q-learning agent in discrete state space without function approximations. In addition, this article also proposes an adaptive deep reinforcement learning energy management scheme for practical hybrid-electric propulsion systems operating in changing environments.

Metallized Film Capacitors (MFC) are vital devices in many important fields such as energy, transportation, and aviation, whilst Digital Twin (DT) technology opens a new channel to leverage existing data resources of metallized film capacitors. This paper review current knowledge about metallized film capacitors and digital twin, list the key issues, propose frameworks, and provide the outlook to clarify the potential of digital twin’s application in metallized film capacitors. First, based on the development history and research status of metallized film capacitors, this review sorts out the key research issues of data utilization. Then, the connotation and typical characteristics of the digital twin definition are combed and refined, and the typical architecture of digital twin implementation is presented. Furthermore, the overall application architecture of digital twin in metallized film capacitors is constructed, and the technology system of each application scenario and the role of digital twin are analyzed. Finally, the main challenges in the application of the digital twin in metallized film capacitors and the future development directions are discussed. This review promotes the performance improvement, cost reduction and application expansion of metallized film capacitors, which can be used as a guide for the application of digital twin in other power equipment of energy system.

Linear Fresnel collectors offer great potential for producing solar heat for industrial processes, both on a small and large scale. Thermal oil, pressurized water, or steam are used as heat transfer fluid in most applications, due to their suitable thermal properties. A heat exchanger is required for thermal power delivery to the user unless the heat transfer fluid is directly used as a medium in the industrial process. For those industrial applications using hot air as a process fluid, direct air heating inside linear Fresnel collectors can be an interesting solution aiming at simplification, cost reduction, and environmental and safety benefits. In this experimental study air is heated inside a commercial small-scale Linear Fresnel collector row of 79.2 m2 active surface, demonstrating the viability of direct air heating up to 500 °C at its outlet. A commercial turbocharger pressurizes the air and reduces the blowing power. The purposely designed test campaign carried out in Madrid (Spain) during spring and summer seasons allowed the experimental contrast of a detailed 1D opto-thermal numerical model. Both static and purposely developed dynamic models of the receiver tube have been scrutinized and tested. The models and the experimental information allowed for the accurate characterization of both thermal losses and optical efficiency.

Background Operating rooms (ORs) contribute up to 30% of a hospital's waste, are very resource-intensive, and thus provide an opportunity for improvement. Methods A narrative review was conducted, searching MEDLINE, EMBASE, and ProQuest databases. The study included 78 of the 108 published articles. Results The researchers identified and categorized articles according to the following major themes: Committee and Leadership; Waste Reduction; Segregating OR waste; Minimizing unnecessary devices and packaging; Reducing energy consumption; Choosing anesthetic gases; Education; Reducing water consumption; Different surgical venues; Donating medical supplies. Formation of an OR committee or a hospital Green Team dedicated to environmentally sustainable initiatives can significantly improve health care's impact on the environment while saving money. Changes in supply chain with preferences for reusable devices, effective recycling, repurposing instruments, and donating items can all be effective means of diverting waste away from landfills. Reducing unnecessary packaging and instruments would eliminate excess in the waste stream. Curtailing energy and water usage results in cost and environmental savings. Surgical venue (inpatient vs. outpatient surgical center) can also contribute to waste. Transitioning away from certain inhaled anesthetics can minimize greenhouse gas impact. Education to all levels in the health care system is important to drive change and maintain change. Conclusion Optimizing efficiency and decreasing waste generation can have a positive impact on the environment and can be accompanied by cost reduction. Because the field of sustainability in health care is young but burgeoning, increased research is needed to support evidence-based approaches.

Hydrogen has been identified as a potential gamechanger and ambitious national targets have been announced by many governments around the world. However, the lack of clear policy signals at the country level remains a barrier and significant cost reduction progress is unlikely to be made unless the issue is addressed. The paper aims to assess whether current UK energy policies support an economic case for low-carbon and competitive H2 production. A financial model is developed for hypothetical H2 projects based in the UK. Price assumptions are assigned to a specific set of policies in combination with the key technical considerations for H2 production and estimated return. The study concludes that H2 development featuring electrolysers or carbon capture and storage cannot rely on market forces alone to reach full commercialisation and competitiveness in the UK. While policies improve the economic case for H2 in some key areas, existing frameworks are not ambitious enough to advance the transition to low carbon options such as Blue and Green H2. Moreover, current policies do not sufficiently disincentivise investments in emission-intensive alternatives.

In this paper we address an optimization problem that arises in two- or three-echelon distribution network design whereby there is an interplay between the production and transfer schedule of semi-customizable products and their delivery under tight time windows. It is motivated by a real-world problem of optimizing the joint newspaper last-mile distribution network for SPDL (Sao Paulo Distribution and Logistics), a dedicated logistics provider established by the two major newspaper publishers in Sao Paulo, Brazil. Such collaborative logistics comprises servicing a very large number of customers in the urban setting of a large metropolitan area. The last-mile delivery is performed daily by a fleet comprising several hundreds of motorized vehicles (mainly motorcycles and light vans) that may originate either from a distribution center (that receives and consolidates different newspapers originating at the two printing sites for the delivery routes) or from informal transit points to where they are transferred, forming a multi-echelon delivery system. The resulting problem is complex not only due to its dimension but also as it involves three main types of decisions that should be taken simultaneously: the number and location of the distribution centers (DCs), the optimal synchronization of the transfer schedule of newspapers from the two printing sites to the selected DCs and the newspaper last-mile delivery. The main theoretical contribution of this work is a multi-stage solution approach whose core is a schedule-to-distribution model that allows integrating printing ramp-up constraints with the transfer shipment schedule and distribution routes. Together with a facility location model and a two-tier delivery districting, we could redesign the multi-echelon distribution operation in a more cost-efficient manner while ensuring the current service level to be maintained without service disruptions. This approach allowed us to obtain a new optimized network configuration and the corresponding delivery clusters with vehicle type choice as well as the optimal transfer schedule that yielded a significant cost reduction of nearly 18%.

This paper presents a thorough parametric analysis of an earth-air heat exchanger (EAHE) that reveals optimal parameters for minimizing the cost of central air conditioning in a hot and dry climate. A mathematical model with the aid of MATLAB is developed to optimize different parameters including length, diameter, and number of pipes. The performance of the selected cooling system is evaluated in terms of compressor power consumption, overall power savings, overall cost reduction, and payback period. As a case study for our analysis, a 25-TR air-conditioning system was chosen to cool an operation room in a hospital in Egypt. The maximum reduction in compressor power consumption is estimated to be 44%. Moreover, the reduction in the annual costs is estimated to be 16.6% with a payback period that increases as the number of pipes increases.

The transportation sector is one of the largest fuel consumers and pollutant contributors worldwide. The International Maritime Organization predicts that the greenhouse gas (GHG) emissions from transportation will be increasing significantly until 2050, driven by the growth in global maritime trade. Managing logistics distribution routes is considered a possible approach for controlling GHG emissions. This study aims to implement a green logistics concept in the logistics distribution of petroleum products—gasoline, kerosene, and diesel—in eastern Indonesia, whose supply sources are refineries located in Balikpapan and Kasim. A multi-objective approach is used to implement the green logistics concept. Multi-objective optimization is conducted using the AIMMS software to optimize a logistics system consisting of a multi-depot, multi-product, and heterogeneous fleet. The optimization is performed to determine the best logistics route and the amount of products delivered using certain types of fleets to minimize transportation cost and GHG emissions using constant speed. In addition, this study also investigates the effect of variable speed on cost and CO2 emissions. For the constant speed case, the distribution routes obtained for the minimizing cost scenario tends to maximize the utilization of transit terminals while in the minimizing emissions scenario tends to deliver directly to the distribution centers, so the route decision in multi-objective optimization scenario is combination of the two. The multi-objective optimization results an 11% cost reduction and a 17% GHG emission reduction compared with the current values. The comparison between constant and variable speed reveals that the variable speed is preferred to constant speed as it gives lower emissions with slight changes in cost.

The dissemination of fuel-cell vehicles requires cost reduction of hydrogen refueling stations. The temperature of the supplied hydrogen has currently been cooled to approximately −40 °C. This has led to larger equipment and increased electric power consumption. This study achieves a relaxation of the precooling temperature to the −20 °C level while maintaining the refueling time. (1) Adoption of an MC formula that can flexibly change the refueling rate according to the precooling temperature. (2) Measurement of thermal capacity of refueling system parts and re-evaluation. Selection from multiple refueling control maps according to the dispenser design (Mathison, et al., 2015). (3) Calculation of the effective thermal capacity and reselection of the map in real time when the line is cooled from refueling of the previous vehicle (Mathison, and Handa, 2015). (4) Addition of maps in which the minimum assumed pressures are 10 and 15 MPa. The new method is named MC Multi Map.

In this study, we investigate the production decision making of a manufacturer, considering the sequential use of raw and recycled materials in a single production process, in which the production setup notably influences the product conformance. Compared with raw materials, recycled materials are less expensive but may not have a sufficiently stable quality, which may lead to a variable setup time. We consider the maximum allowed setup time for recycled materials to mitigate the risk of a prolonged setup time. By minimizing the expected cost per unit time, we determine the manufacturer’s lot size for the raw materials in settings in which the maximum allowed setup time is exogenous and endogenous and the lot size of the recycled materials is exogenous. The results of the numerical analyses demonstrate that the maximum setup time and lot size of the recycled materials can serve as cost reduction drivers for the manufacturer. Furthermore, production with raw and recycled materials involves a lower cost than production with raw materials owing to the lower purchase cost and average setup time incurred when using recycled materials.

BACKGROUND CONTEXT Improving value is an established point of emphasis to reduce the rapidly rising health care costs in the United States. Back pain is a major driver of costs with a substantial fraction caused by lumbar radiculopathy. The most common surgical treatment for lumbar radiculopathy is microdiscectomy. Research is sparse regarding variables driving cost in microdiscectomies and often limited by cost data derived from payer-based Medicare data. PURPOSE To identify targets for cost reduction by determining variables associated with significant cost variation in microdiscectomies, using cost data derived from the Value Driven Outcomes tool and actual system costs. STUDY DESIGN Single-center, retrospective study of prospectively collected registry data. PATIENT SAMPLE Six hundred twenty-two patients identified by CPT code and manually screened for initial, unilateral, single-level lumbar discectomy performed between 2014 and 2018 at a single institution. OUTCOME MEASURES Primary outcome measures include total direct cost, clinical length of stay, and OR minutes. Total Direct Cost was further differentiated into facility and nonfacility costs. METHODS Univariate and multivariate generalized linear models (GLM) were used to identify variables associated with variation in primary outcome measures. Costs were normalized by mean cost for patients with normal body mass index (BMI) and a healthy American Society of Anesthesiologists (ASA) classification. Average marginal effects were reported as percentage of normalized costs. RESULTS Advanced age, male gender, Hispanic, black, unemployment, obesity, higher ASA class, insurance status, and being retired were positively associated with costs in univariate analysis. Asian, Native American, outpatient procedures, and being a student were associated with decreases in costs. In multivariate analysis, we found that obesity led to higher average marginal total direct (9%), total facility (15%), and facility OR costs (22%), as well as 24 more OR minutes per surgery. While being overweight was not associated with greater total direct costs, it was associated with higher total facility (8%), and facility OR costs (12%), with 11 more OR minutes per surgery. Age was associated with a longer LOS but not with OR costs. As expected, outpatient surgical costs, LOS, and OR time were significantly lower than inpatient procedures. Severe systematic disease was associated with greater total and nonfacility costs. In addition, Medicare patients had higher facility costs (14%) compared to privately insured patients. CONCLUSIONS Significant drivers of total direct cost in multivariate GLM analysis were obesity, severe systemic disease and inpatient surgery. Average LOS was increased due to age and inpatient status, conversely it was decreased by unemployment and retirement. Significant variables in OR time were male sex, Hispanic race and both obese and overweight BMIs.

The growing interest in integrating variable renewable energy resources (RES), besides global concerns about greenhouse pollution, brings multiple challenges for eco and environmentally-friendly operation of systems. Meanwhile, the simultaneous energy supply can improve energy efficiency and mitigate the fluctuation of RES compared with a single-energy system. Therefore, this paper seeks to investigate the optimal scheduling of heating, power, and hydrogen-based microgrid incorporated with RES and plug-in electric vehicles (PEV). The fuel-cell-based hydrogen and electrolyzer facilities are integrated into the multi-energy system to investigate the power-to-hydrogen and hydrogen-to-power technologies in the model. Besides typical electric and thermal loads, the proposed system can directly sell hydrogen to hydrogen-based industrial applications. The PEV as a flexible resource is employed to facilitate the integration of solar energy. Due to the substantial uncertainty from solar energy, price, load, and EVs' arriving and departing times, the risk management of the model based on the conditional value-at-risk is developed to show the operator's behavior against the random inputs and their risk. Results show that integrating the hydrogen storage and plug-in electric vehicle in the model results in a daily cost reduction of up to 9.28%.

Low-temperature, atmospheric pressure plasma presents a new, inexpensive, and environmentally friendly method of water purification. For long duration crewed space missions, a novel water purification system that does not rely on consumable filters and chemicals would be desirable. Plasma systems provide a viable option for these missions, but their operation and designs need to be optimized and compared to existing technology. For this application, gas and power usage are key limiting factors. In this work, water contaminated with methylene blue is purified with plasma. The rate of purification, gas flow usage, and power consumption are compared for multiple devices. A single atmospheric pressure plasma jet is compared with jet array configurations and a novel, 3D printed “plasma sheet” design that expands the size of the plasma surface area. A resource gauge parameter was developed to compare the resource usage and purification rate of each device, and this parameter showed that the plasma sheet was able to improve the rate of purification without increasing resource usage. Additionally, two types of jet arrays were designed that demonstrated the need to exceed a minimum energy and flow rate threshold to maintain effective treatment. A low cost jet was also developed that showed suitable treatment results with a two order of magnitude cost reduction. Finally, a figure of merit was discussed to compare the best performing plasma device with the urine processor assembly used on the International Space Station.

To achieve carbon neutrality by 2060, decarbonization in the energy sector is crucial. Hydrogen is expected to be vital for achieving the aim of carbon neutrality for two reasons: use of power-to-hydrogen (P2H) can avoid carbon emissions from hydrogen production, which is traditionally performed using fossil fuels; Hydrogen from P2H can be stored for long durations in large scales and then delivered as industrial raw material or fed back to the power system depending on the demand. In this study, we focus on the analysis and evaluation of hydrogen value in terms of improvement in the flexibility of the energy system, particularly that derived from hydrogen storage. An electricity–hydrogen coupled energy model is proposed to realize the hourly-level operation simulation and capacity planning optimization aiming at the lowest cost of energy. Based on this model and considering Northwest China as the region of study, the potential of improvement in the flexibility of hydrogen storage is determined through optimization calculations in a series of study cases with various hydrogen demand levels. The results of the quantitative calculations prove that effective hydrogen storage can improve the system flexibility by promoting the energy demand balance over a long term, contributing toward reducing the investment cost of both generators and battery storage and thus the total energy cost. This advantage can be further improved when the hydrogen demand rises. However, a cost reduction by 20% is required for hydrogen-related technologies to initiate hydrogen storage as long-term energy storage for power systems. This study provides a suggestion and reference for the advancement and planning of hydrogen storage development in regions with rich sources of renewable energy.

The reduction of gained heat, heat peak shifting and the mitigation of air temperature fluctuations are some desirable properties that are sought after in any thermal insulation system. It cannot be overstated that these factors, in addition to others, govern the performance of such systems thus their effect on indoor ambient conditions. The effect of such systems extends also to Heating, Ventilation and Air-conditioning (HVAC) systems that are set up to operate optimally in certain conditions. Where literature shows that PCMs and natural materials such as wood-shavings can provide efficient passive insulation for buildings, it is evident that such approaches utilise methods that are of a degree of intricacy which requires specialist knowledge and complex techniques, such as micro-encapsulation for instance. With technical and economic aspects in mind, an amalgam of PCM and wood-shavings has been created for the purpose of being utilised as a feasible thermal insulation. The amalgamation was performed in the simplest of methods, through submerging the wood shavings in PCM. An experimental procedure was devised to test the thermal performance of the amalgam and compare this to the performance of the same un-amalgamated materials. Comparative analysis revealed that no significant thermal gains would be expected from such amalgamation. However, significant reduction in the total weight of the insulation system would be achieved that, in this case, shown to be up to 20.94%. Thus, further reducing possible strains on structural elements due to the application of insulation on buildings. This can be especially beneficial in vernacular architectural approaches where considerably large amounts and thicknesses of insulations are used. In addition, cost reduction could be attained as wood shavings are significantly cheaper compared to the cost of PCMs.

The traditional tourism industry is in urgent need of digital technologies for cost reduction and efficiency enhancement. Blockchain, as an emerging technology, is promising to reform the tourism industry because it provides a trustworthy platform to link the tourism company and tourists. However, the existing blockchain-based smart tourism solutions are either conceptual or limited in solving the fundamental tourism challenges. In this paper, we propose BlockTour, a blockchain-based smart tourism platform with dedicated solution to address the challenges and real-world prototype deployment. In particular, we design the overall system architecture of BlockTour to link the tourists and attractions in a trustworthy way. Moreover, an efficient consensus mechanism is designed with incentives for the tourists to explore more attractions. Finally, we implement BlockTour and conduct extensive experiments for performance evaluation. The experimental results indicate that BlockTour is a practical and high-performance smart tourism platform.

On the basis of scrap metal recycling, the shredding process transforms a large variety of objects composed predominantly of steel in crunched scrap. The main equipment used in this process is called shredder: a device consisting of several hammers attached in a horizontal rotor. Due to high efforts involved in the transformation process, the maintenance is an essential aspect to ensure the continuity of the shredder operation. A non-efficient maintenance policy can have negative consequences for the shredder performance, whose failure can stop all downstream processes for which it provides the basic input (crunched scrap). In order to improve the performance of the steel production line, we are introducing an opportunistic inspection policy that makes use of the crushed scrap buffer level. The policy guides the execution of an inspection after a time T of continuous operation, when the system fails, when the buffer is full or empty, or when the opportunity criterion (operation time ≥ t AND buffer level ≥ h) is verified, whichever occurs first. At an inspection, the shredder is stopped, the hammers are inspected, and the failed and defective ones are replaced by new units. A discrete-event simulation model was developed and applied to the context of a real steel production line of a company. The optimal opportunistic inspection policy was obtained, and its performance was compared with that of the policy currently adopted by the company. The results showed the possibility of obtaining significant economic savings. A sensitivity analysis showed a cost reduction of around 95 %.

Although developing countries typically deal with the challenge of mobilizing investments for adding new generation and transmission capacity to cope with high demand growth, there are often opportunities to enhance operation of existing generators and extract significant cost reduction as well as the ability to meet greater demand. This is particularly relevant for the Nigerian power system that has 13 GW of installed capacity but could meet only 5.2 GW of peak demand in 2018 at an average capacity utilization of 27% of its thermal (mostly gas) generation fleet. There are simple steps that can be adopted to restore merit-order based dispatch that can immediately yield an operational cost reduction. Increased plant availability, gas supply to power plants, and removal of uneconomic take-or-pay obligation are increasingly onerous tasks, but with commensurate significantly higher payoffs. We have used a dispatch analysis model to show that merit-order based dispatch within the current constraints can yield an annual benefit of $29 million or 4% of variable costs. With the removal of physical availability constraints around plants and gas supply, benefits increase by an order of magnitude to $309 million, or 19% of total annual costs. If it is possible to get rid of the uneconomic take-or-pay obligations, benefits would further increase to $579 million or over 30% of total annual costs. These are major findings especially if we consider these in the context of tremendous financial stress in the power sector. Although we do not estimate the cost of implementing these measures, there are very little hard investments needed in some of these cases such as establishing a strict merit-order based dispatch or enhancing operational practices to improve plant and gas availability. There are indeed difficult commercial and institutional issues when it comes to renegotiating take-or-pay contracts, albeit the massive benefits in excess of half a billion dollar per year should make it a worthwhile undertaking. Removal of operational and commercial constraints could also allow the Nigerian power system to meet increased demand to the benefit of unserved residents or businesses, and pave the way towards increased penetration of variable renewable energy (VRE) resources. We have shown that an addition of 500 MW solar capacity in the current system will earn reasonable return on investment between 4% and 9% and help to meet increased demand. However, an important precondition for adding large-scale solar is to raise the spinning reserve capability in the system through additional investments in flexible resources, namely, open cycle gas turbines (OCGT), pumped storage hydro or battery storage systems.

Co-digestion is a well-established strategy to maximise the capacity of anaerobic digestion in wastewater treatment plants (WWTPs). Many tools have been developed to optimise the blend composition. However, the logistics associated with each component of the blend remain a relatively unexplored field, which can yield significant planning challenges. In this paper, an ant colony optimisation based approach is proposed to address these challenges. The proposed algorithm maximises an objective function composed of a first term related to the quality of the sludge and a second term related to the distance between the sludge generator and the anaerobic co-digester. The algorithm successfully optimises the blend composition by considering the related logistics, achieving an optimum blend with an approximately 18% volume of co-substrate. The approach presented here has been used to plan co-digestion using real data from an actual sanitation network composed of 13 WWTPs in the area of the Besos river basin in Catalonia, and an optimised co-digestion planning strategy with a waste management cost reduction of 77% was obtained

Introduction Operating room (OR) efficiency is a crucial component in the delivery of high quality, cost-efficient healthcare in orthopedic shoulder arthroplasty, and generally in surgery. Utilizing a dedicated OR team may lead to higher clinical efficiency by potentially reducing total OR time and cost while avoiding operational redundancies or errors. The purpose of this study is to identify specific parameters influencing OR efficiency with a 2-roomed system with dedicated OR staff and evaluate its influence on operational cost of the OR per min. Methods From 2017 to 2018, 348 patients underwent primary shoulder arthroplasty at one institution, that had 2 established OR systems: A traditional “1-room” system (TS) with general OR staff, and a “2-room” shoulder service (SS) with a dedicated OR team. Medical health records were accessed to obtain pertinent study data, which included demographics, surgical indication, and time-points per surgical case. Anesthesia preparatory time (APT) was time from patient OR entry to skin incision; surgery time (ST) – from skin incision to skin closure; conclusion time (CT) – from skin closure to patient exiting OR; and turnover time (TT) – time from 1 patient's exiting to the next patient's admittance into the OR. Nonoperative time was a summation of APT, CT, and TT, while Total OR time comprised of nonoperative time and ST. Cost equivalent per minute OR operation was then used to calculate differences between the 2 interest groups. Results The SS treated 270 patients (77.6%) and TS treated 78 patients (22.4%). The SS demonstrated a 74 minutes decrease in total OR time (116 vs. 190 minutes) when compared to the TS (P Conclusion A dedicated OR team using 2 ORs improves both clinical efficiency (decreases total OR time) and reduces cost (decreases total OR cost) - despite having more staff members and associated staffing costs - compared to a traditional 1-room system. When surgeon-specific factors were removed, the largest reduction in OR cost was associated with decrease in turnover time. Level of Evidence Level III.

Kombucha is a functional tea brewed through a symbiotic culture of bacteria and yeast (SCOBY). It is applicable to various industrial sectors due to its several noteworthy features. Therefore, this study aims to elucidate the following technological aspects of kombucha/SCOBY: (a) the effect of its production parameters on different scales, (b) microbiota features and factors that affect biofilm formation and fermentation so as to demonstrate its potential applications in different industrial sectors, and (d) how its consumption affects human health according to evidence collected in literature. Its production seldom occurs on an industrial scale and studies assessing its large-scale fermentation process are scarce. Various industrial sectors have benefited from SCOBY, such as the food industry, biotechnological processes and biomedicine. However, industrial applications require optimization of some parameters, such as specific equipment for product standardization aimed at cost reduction and process profitability.

The purpose of this article is to identify barriers, drivers, and the structure of the relationships that support industrial symbiosis initiatives in a network of Brazilian manufacturing companies. Two steelmaking plants are the anchor tenants of the network comprising a cement manufacturer, a thermoelectric generation plant, a lead ingots manufacturer, a zinc ingots manufacturer and refractory liner manufacturer, totaling eight relationships. The companies mutually exchange approximately 300,000 tons of by-products per year, comprising coal ash, mill scale, electric arc furnace dust, steam, zinc sludge, lead sludge, and refractory lining leftover, totaling eight dyadic or triadic relationships. The results of the study show that in three relationships, economic barriers exist (excessive processing or logistic cost). In four, internal barriers exist (risk of discontinuity and lack of research). In five, a technical barrier exists, the imbalance between generation and consumption. In seven, the drivers are cost reduction, new products or sources of revenue, and legal requirements. Environmental drivers (increasing the life of deposits or landfills) are present in five relationships. As for the structure, three relationships are one-way, whereas five are closed-loop, that is, involving direct and reverse transfers among partners.

Objectives Various strategies to address healthcare spending and medical costs continue to be debated and implemented in the United States. To date, these efforts have failed to adequately contain the growth of healthcare cost. An alternative strategy that has elicited rising interest among policymakers is budget caps. As budget caps become more prevalent, it is important to identify which features are needed to ensure success, both in terms of cost reduction and health improvement. Methods We explored the impacts of different features of budget caps by comparing hypothetical service level and global budget caps across 3 annual budget cap growth strategies over a 10-year timeframe in 2005-2015 for 8 of the most commonly occurring conditions in the United States. Health was assessed by a measure of disease burden (disability-adjusted life years). Results The results indicate that budget caps have the potential for creating savings but can also result in patient harm if not designed well. As a result of these findings, 5 principles were developed for designing budget caps and should guide the use of budget caps to address medical spending. Conclusions As public discussion grows about the use of budget caps to constrain health spending, it is critical to recognize that the budget cap design and the resulting healthcare provider behavior will determine whether there is potential harm to public health. Budget cap design should consider variability at the condition level, including patient population, improvements in health, treatment costs, and the innovations available, to both create savings and maximize patient health. In assessing the impact of healthcare spending caps on costs and disease burden, we demonstrate that budget cap design determines potential harm to public health.

There is an urgent need to develop technologies which enable the conversion of biomass into liquid biofuels to fill the gap between limited fossil fuel supplies and increasing worldwide demand. In order to achieve the EU 2030 vision of at least 15% of the fuels used in the road transportation sector will be biofuels derived from non-food biomass feedstocks, the R&D of clean, inexpensive, highly end-user compatible biofuels from a virtually inexhaustible source of biomass should be pursued to make breakthroughs in cost-effective biomass to liquid biofuels (BTL) technologies. Thus, an innovative, consolidated, and sustainable technology using a hybrid digestion-gasification process integrated with membranes to produce next generation bio-alcohols from different biomass feedstocks was designed. The proposed concept was theoretically estimated to achieve an overall BTL efficiency of 44% and a cost reduction for bioalcohol production of 18.6%. Moreover, this technology can potentially achieve an overall CO2 emission reduction of > 75% for road transport based on the preliminary analysis.

Purpose To evaluate time-driven activity-based costing (TDABC) in interventional radiology for image-guided vascular malformation treatment as an example. Materials and Methods Retrospective analysis was performed on consecutive vascular malformation treatment cycles [67 venous malformations (VMs) and 11 arteriovenous malformations (AVMs)] in a university hospital in 2018. All activities were integrated with a process map, and spent resources were assigned accordingly. TDABC uses 2 parameters: (i) practical capacity cost rate, calculated as 80% of theoretical capacity, and (ii) time consumption of each resource determined by interviews (23 items). Thereby, the total costs were calculated. Treatment cycles were modified according to identified resource waste and TDABC-guided negotiations with health insurance. Results Total personnel time required was higher for AVM (1,191 min) than for VM (637 min) treatment. The interventional procedure comprised the major part (46%) of personnel time required in AVM, whereas it comprised 19% in VM treatment. Materials represented the major cost type in AVM (75%) and VM (45%) treatments. TDABC-based treatment process modification led to a decrease in personnel time need of 16% and 30% and a cost reduction of 5.5% and 15.7% for AVM and VM treatments, respectively. TDABC-guided cost reduction and TDABC-informed negotiations improved profit from −56% to +40% and from +41% to +69% for AVM and VM treatments, respectively. Conclusions TDABC facilitated the precise costing of interventional radiologic treatment cycles and optimized internal processes, cost reduction, and revenues. Hence, TDABC is a promising tool to determine the denominator of interventional radiology's value.

Titanium alloys have created a niche in mechanical parts that requires high strength with light-weight. Nowadays, parts of exotic vehicles are made from titanium alloys which contribute to the high cost of these cars. Shape and model optimization have played important roles in cost reduction in contrast to the choice of high-end materials usually as a factor of the weight. This work considers the impact of shape optimization on Ti-6Al-4 V used as connecting rod in a 500 cc engine. A model of the connecting rod was created using Autodesk Inventor; the various forces and constraints were calculated which were then used in ANSYS to simulate the failure. Shape optimization was achieved by optimizing the clearance at the crank end. The optimized model yielded 11.7% reduction in weight, lower deformation and stress distributions. It was discovered that shape optimization by modifying the clearance at the crank end offered the best output.

Hydrogen-specific policies are required to accelerate the adoption of low-carbon hydrogen. In this study, a range of economic instruments and regulations were incorporated explicitly to optimize a hydrogen supply chain. The effectivenes of policies aiming to enhance the financial viability of low-carbon hydrogen production was quantified. A spatially explicit, multi-period cost optimization model was developed for light duty hydrogen hydrogen vehicle deployment in British Columbia under three demand scenarios. Subsidies and regulations were coupled to current provincial policies (a carbon tax and a low carbon fuel standard). The results indicated that production tax credits and electricity incentives were up to 24 times more effective in facilitating low-carbon hydrogen production compared to capital subsidies, bans on steam methane reforming or the adoption of higher carbon taxes. The strategic deployment of policies over time was found to be more effective than cumulative subsidies.

Insulin pumps are the most consistent and accurate means of regulating blood glucose levels in Types 1 and 2 diabetes. However, the technology is underutilised due to very high costs. A typical insulin pump costs US$6500, which makes this gold standard of care inaccessible to many, reducing equity of access to care. Since insulin pumps were first introduced, the simple hardware has not changed significantly. Pump manufacturers couple the low-cost and simple hardware with their own software, removing consumer choice and locking value into the product. Using both a traditional motor-driven and novel spring-loaded approach, insulin pump hardware can be replicated for US$100. Initial testing of the traditional motor-driven prototype proves the low-cost approach has comparable accuracy to commercially available pumps, with 85.1% of basal doses delivered within 5% of target. The results obtained indicate pump hardware and software can be separated with no significant loss in accuracy. If a separate market for pump software is established, costs can be driven down through market pressure given the increasing access to relatively extensive mobile and cloud computing. If open-source software is made accessible, a complete pump could be offered for US$100. A 98.5% cost reduction would drastically improve pump accessibility, particularly in developing nations, and could lead to a global improvement in diabetes treatment, outcomes and costs.

The paper deals with the issue relating to the improvement of the production process through the use of checkpoints. Quality control points used in an industrial enterprise manufacturing oil pans for heavy vehicles are discussed. The study aimed to present a proposal for a method for analyzing the effectiveness of individual control methods used as part of quality control in the manufacturing process of a product and to analyze the relationship between the type of quality control methods and their contribution to the detection of nonconformities of the product - an oil pan. By locating the control point with the highest share of product nonconformity detection, it is possible to take improvement actions - reducing control points by less effective ones. This action will contribute to cost reduction and shortening of the production process time. Due to the increasing demands on the efficiency and effectiveness of control points of automotive powertrain components, this issue is important and topical.

Nowadays, reducing total costs while enhancing customer satisfaction is a major task for many supply chain systems. To deal with this issue, the ‘Physical Internet’ (PI) paradigm can be represented as a potential replacement for the current logistics system. This paper devoted the cost reduction and lead time improvement in a PI-SCN using a hybrid framework based on an artificial neural network (ANN) and an improved slime mould algorithm metaheuristic. To address the performance of the proposed framework, a real-case study in Morocco is considered. The new trainer ISMA’s performance has been investigated regarding five recent metaheuristics. The experimental results highlight the effectiveness of ISMA according to other metaheuristics for training Feed-forward Neural Networks (FNNs) to converge speed and to avoid local minima.

Lean manufacturing is one of the techniques that many major businesses are attempting to implement to stay competitive in the international market. This work aims to improve cost reduction, standardization, and assembly cycle time optimization of a packaging machine using lean techniques. Amongst various tools of lean manufacturing techniques like waste elimination, standardized work approach, visual management, etc., are used. Among the eight types of waste, waste related to the packaging machine like incorrect processing, waiting, and unused employee creativity were identified and reduced. Kaizen is done for value engineering purposes. The work instruction manual is created to avoid the waste of incorrect processing and optimize the machine’s cycle time.

The significant objective of current examination will be to evaluate the usefulness of ceramic tile waste (CTW) as admixture for fine sand, and concentrated to expand the engineering properties of fine sand to make it proficient to reduced cross section of embankment for road construction. This research paper includes laboratory experimental work, software work and cost analysis work. The diverse laboratory experiments were executed on fine sand with direct mixing of fine sand of diverse dry densities 1.50 gm/cc, 1.55 gm/cc and 1.58 gm/cc (M.D.D.) and diverse percentage 0%, 2%, 4%, 8% and 12% by dry weight of fine sand of CTW material having particles size range between 2.36 mm and 4.75 mm. Geotechnical software was used for stability analysis of road embankments of various heights of 6.0, 7.5 and 9.0 m. The rate analysis was done manually according to B.S.R. 2014, P.W.D., Rajasthan, India and cost reduction ratios were calculated. The reduction in cross-section of road embankment was tremendous and the cost of the construction was also reduced to a good extent.

Objectives We develop a patient prioritization scheme for treating patients infected with hepatitis C virus (HCV) and study under which scenarios it outperforms the current practices in Spain and Chile. Study design We use simulation to evaluate the performance of prioritization rules under two HCV patient cohorts, constructed using secondary data of public records from Chile and Spain, during 2015–2016. Methods We use the results of a mathematical model, which determines individual optimal HCV treatment policies as an input for constructing a patient prioritization rule, when limited resources are present. The prioritization is based on marginal analysis on cost increases and health-outcome gains. We construct the Chilean and Spanish case studies and used Monte Carlo simulation to evaluate the performance of our methodology in these two scenarios. Results The resulting prioritizations for the Chilean and Spanish patients are similar, despite the significant differences of both countries, in terms of epidemiological profiles and cost structures. Furthermore, when resources are scarce compared with the number of patients in need of the new drug, our prioritization significantly outperforms current practices of treating sicker patients first, both in terms of cost and healthcare indicators: for the Chilean case, we have an increase in the quality-adjusted life years (QALYs) of 0.83 with a cost reduction of 8176 euros per patient, with a budget covering 2.5% of the patients in the cohort. This difference slowly decreases when increasing the available resources, converging to the performance indicators obtained when all patients are treated immediately: for the Spanish case, we have a decrease in the QALYs of 0.17 with a cost reduction of 1134 euros per patient, with a budget covering 20% of the patients in the cohort. Conclusion Decision science can provide useful analytical tools for designing efficient public policies that can excel in terms of quantitative health performance indicators.