Performance Of Supply Network Research Articles

Fuzzy Control of Pressure in a Water Supply Network Based on Neural Network System Modeling and IoT Measurements

As hydroenergetic losses are inherent to water supply systems, they are a frequent issue which water utilities deal with every day. The control of network pressure is essential to reducing these losses, providing a quality supply to consumers, saving electricity and preserving piping from excess pressure. However, to obtain these benefits, it is necessary to overcome some difficulties such as sensing the pressure of geographically distant consumer units and developing a control logic that is capable of making use of the data from these sensors and, at the same time, a good solution in terms of cost benefit. Therefore, this work has the purpose of developing a pressure monitoring and control system for water supply networks, using the ESP8266 microcontroller to collect data from pressure sensors for the integrated ScadaLTS supervisory system via the REST API. The modeling of the plant was developed using artificial neural networks together with fuzzy pressure control, both designed using the Python language. The proposed method was tested by considering a pumping station and two reference units located in the city of João Pessoa, Brazil, in which there was an excess of pressure in the supply network and low performance from the old controls, during the night period from 12:00 a.m. to 6:00 a.m. The field results estimated 2.9% energy saving in relation to the previous form of control and a guarantee that the pressure in the network was at a healthy level.

New software to analyze hydraulic incidents in Algeria

Fifteen percent of the total volume produced is lost, which has become a major problem for water resource management in Algeria. The number of high leakages reduces the performance of the drinking water supply network. The disturbance of the drinking water supply observed by the citizens resulted from several incidents occurring mainly on the axis of production or distribution (e.g., breakage, leakage, pollution, electrical problems, and drought). To manage these incidents and for water distribution monitoring in the high-level strategic plan, monitoring and control software was developed for the Algerian Water Company (ADE). This software is an essential tool that helps managers of water resources to monitor the water supply situation throughout the national territory to ameliorate water public services. This dynamic software has been in use since 2016.

A production bounce-back approach in the Cloud manufacturing network: case study of COVID-19 pandemic

ABSTRACT Industry 4.0 paradigm has enabled manufacturing systems with reformations for Cloud-based manufacturing business models. This reformation can create resilient structures as an inevitable opportunity for manufacturing supply networks. This is achieved by using service composition capabilities in Cloud manufacturing network which significantly enhances supply network performance when encountering disruptions. Focusing on redundancy as one of the most effective approaches to resiliency, a new model for manufacturing service composition is proposed. The model considers a minimum level of subentropy when responding to the demands at the process level while controlling the entropy overall at supply network level. This creates a balanced policy for entropy at the network level, and subentropies at the process level to both fulfill an optimal redundancy for disruption fulfillment and controling the complexity throughout the network. A case study is considered for manufacturing ventilator production COVID-19 pandemic. The capabilities of the proposed model for optimal application of unused firm capacities from other supply networks like military and university research groups have been discussed. The proposed model is also investigated for fulfillment of disruptions like COVID-19 equipment supply network with mentioned capabilities. These capabilities fulfill the transition of manufacturing business models to a service-oriented paradigm with resilient structures.

Proposing a model for a resilient supply chain: A meta-heuristic algorithm

The resilient supply chain considers many capabilities for companies to overcome financial crises and to supply and distribute products. In this study, we address the allocation of inventory distribution for a distribution network, including a factory, a number of potential locations for distribution centers and a number of retailers. Customers demand is assumed to be certain and deterministic for all periods but time varying in the limited planning horizon. The proposed model in this research is a linear complex integer programming model with two-objective functions. The first objective function minimizes the total costs of the entire distribution system in the planning horizon, and the second objective function seeks to minimize the difference between the maximum and minimum distances traveled by vehicles over the planning horizon. Therefore, the model tries to satisfy the demand and at the same time reduce costs using the best route transportation option configuration and transportation option. The routing problem is developed, and as the problem is a NP-hard problem, a meta-heuristic method is used to solve it. In this model, the demand volume for each customer in a period of the network, vehicle capacity, factory capacity, constant transportation cost, variable transportation cost, etc., are considered as factors affecting the model. The results show that the model proposed in the network can be used as a lever to improve the performance of the financial economic supply network through saving in routes.

Enhanced Variable Neighborhood Search-Based Recovery Supplier Selection for Post-Disruption Supply Networks

With the increasing reliance on global sourcing and the growth in the likelihood of disruptive incidents, today’s supply networks are more prone to unexpected natural and man-made disruptive events. In order to alleviate the losses caused by these disruptive events, when a large-scale event disrupts multiple suppliers simultaneously, a single or several critical suppliers should be selected from the disrupted ones to assist them to recover their production as soon as possible. The selection of these recovery suppliers is of great importance in the recovery process of the entire supply network. Thus, this paper proposes a recovery supplier selection method from the view of the supply network structure. Firstly, a tripartite graph-based supply model is proposed to depict a two-stage supply network, which consists of multiple manufacturers and suppliers as well as the diverse product supply-demand interdependence connecting them. To measure the impacts caused by supplier disruptions and to evaluate the effectiveness of recovery supplier decisions, two supply network performance metrics reflecting product supply availability are also given. Then, the recovery supplier selection problem is described as a combinatorial optimization problem. To solve this problem, a heuristic algorithm, with enhanced variable neighborhood search (EVNS) is designed based on the general framework of a variable neighborhood search. Finally, experiments based on a real-world supply network are conducted. The experimental results indicate that the proposed method is applicable and effective.

Linguistic summarization to support supply network decisions

A supply chain network architecture is a key element of designing and modeling a supply chain to better understand the cost and time associated with the distribution of products with available resources and market locations. Due to the large size of combinations for product design and supplier choices; descriptive, predictive and prescriptive analytics are needed to design, control and then improve a supply chain network. Current study is the first instance in the supply network management field using linguistic summarization (LS), a descriptive analytics tool generating natural language-based summaries of raw data with the help of fuzzy sets. This study has developed a LS method for revealing information from a realistic complex network of a bike supply chain, and it produces network description phrases by using fuzzy set theory to model linguistic/textual terms. The truth degree of generated summaries is calculated by fuzzy cardinality-based methods instead of scalar cardinality-based methods to overcome inherent disadvantages. The results of the study are interpreted in two ways: word clouds are used for single objective cases, and list of sentences that exceed a threshold value are used for bi-objective cases. LS-based findings, explanations and strategic decisions are directed at decision support to increase supply network performance, efficiency and sustainability.

Analysis of Performance Indicators for Sustainable Management of Community Drinking Water Networks in Cameroon

The present study on the management of community drinking water networks in Cameroon aims to analyze, using efficiency indicators, the performance of five community water supply networks in the municipalities of Ndu and Kumbo in the North West region, Bandja in the West region and Efoulan and Zoetélé in the South region. The analysis of the said networks was done using technical and financial indicators: primary yield, rate of unpaid invoices, linear distribution loss index, average annual rate renewal network and the maximum connection opening time for new subscribers. The analysis of financial performance was done through the analysis of annual revenues, leading to the conclusion that these six indicators are important for analyzing the performance of community water supply networks. The study demonstrated also the strong influence of overall water consumption, the linear water loss index and annual turnover on the overall performance of the community water supply network.

Using MODELICA for calculating the power requirements of a mid-sized city water supply pumping system

The issue of water supply is one of the fundamental issues of the society, it is one of the pillars without which society would not work. The performance of the Targoviste water supply network has fallen over time, so solutions are being sought to optimize this network. A short description of the current situation has been made in the paper and solutions have been proposed for a certain area of capture and pumping of water to consumers. For the choice of pumps, water supply systems, calculations were made for the selection of system pipes, pumping height, pump motor power, and loss coefficients. With the help of the MODELICA calculation program, simulation of the pumping station was carried out using two separate calculation models by means of boundary conditions established with the help of water sources. The simulation of the water supply system was performed to verify that the pump power is sufficient to ensure the flow of water required by the consumer and to determine the operating mode of the drive system (continuous or intermittent).

Post-earthquake hydraulic analyses of urban water supply network based on pressure drive demand model

This study develops a simulation method of water supply network against earthquakes based on pressure drive demand model. For this purpose, Monte Carlo method is used for the probabilistic seismic simulations and the mean system serviceability is obtained as the final analysis result. In each simulation, a post-earthquake water supply network hydraulic model comes into being as a result of random selection of pipelines status, then the system serviceability is calculated through hydraulic analysis based on pressure drive demand model. In case analysis, we use the developed method and GIARFFE software developed by professor O’Rourke from Cornell University to analyze an urban water supply network performance under different earthquake intensities. The results show that: the results between the developed method and GIRAFFE have the same trends, the developed method needs less number of Monte Carlo simulation than GIRAFFE, and less operation time than the GIRAFFE in a single simulation; a damaged pipeline reduces both of upstream and downstream nodes serviceability in the analysis based on pressure drive demand model.

Is Network Trust Beneficial For Supply Network Resilience? A Simulation Analysis

Trust is widely recognized as a predictor of positive supply network performance in terms of cost reduction and enhanced service level. However, little is known about the effect of trust on supply network resilience, i.e. the ability of the network to cope with perturbations by absorbing the disturbance and/or to quickly recover. This paper overcomes this gap by adopting a recent conceptualization of network-level trust and by developing an agent-based model of supply network, simulating its resilient performance. A simulation analysis is carried out to assess the effect of trust on the resilience of supply networks showing different interdependence structures. Results confirm that trust positively affects supply network resilience. However, we find that the benefit varies across interdependence structures, being almost neglected for supply networks exhibiting a dependent structure. Furthermore, we achieve that the higher the frequency of disruptions, the lower the beneficial effect of trust for supply network resilience.

Supply Chain Network Robustness Against Disruptions: Topological Analysis, Measurement, and Optimization

This paper focuses on understanding the robustness of a supply network in the face of a disruption. We propose a decision support system for analyzing the robustness of supply chain networks against disruptions using topological analysis, performance measurement relevant to a supply chain context, and an optimization for increasing supply network performance. The topology of a supply chain network has considerable implications for its robustness in the presence of disruptions. The system allows decision makers to evaluate topologies of their supply chain networks in a variety of disruption scenarios, thereby proactively managing the supply chain network to understand vulnerabilities of the network before a disruption occurs. Our system calculates performance measurements for a supply chain network in the face of disruptions and provides both topological metrics (through network analysis) and operational metrics (through an optimization model). Through an example application, we evaluate the impact of random and targeted disruptions on the robustness of a supply chain network.

Correlation between strategic and operational risk mitigation strategies in supply networks

A supply network's performance is affected by two types of risk: 1) risk of disruptions that distort the supply network's topology by inactivating certain production facilities or transportation lanes; and 2) risk of variations in a facility's performance that reduce the efficiency of the supply network's flow planning for fulfilling demands. In this paper, we demonstrate that strategic and operational risk mitigation strategies, which neutralize the impacts of disruptions and variations, respectively, are correlated. We consider “Robustness” and “Resilience” at a strategic level to mitigate disruptions and “Reliability” at an operational level to mitigate variations.A mixed integer stochastic mathematical model is developed to simultaneously a) design a robust and resilient topology for supply networks; and b) plan a reliable flow throughout its topology. We solve the model using an example of a profit-based supply network that is constructed by relying on the assumptions that were primarily used in prior studies. A sensitivity analysis of the results from the model indicates that i) the correlation between robustness and resilience is negative; ii) the correlation between robustness and reliability is positive; and iii) the correlation between resilience and reliability is negative.

Inventory routing problem for hazardous and deteriorating items in the presence of accident risk with transshipment option

In this study, we address an Inventory Routing Problem for hazardous and deteriorating pharmaceutical items in a healthcare network. Each hospital's demand is assumed to be deterministic but time varying over a finite planning horizon. Demand can be satisfied through a supply network, either from the main central pharmacy, or from other related hospitals' drugstores by allowing the transshipment option. The medicines deteriorate under a constant rate during the storage period. The proposed model is a bi-objective mixed integer mathematical programming. The first objective aims to minimize the total cost of logistics including ordering, transportation, delivery, pickup, shortage and inventory holding costs. The second objective function attempts to minimize the maximum accident loss during distribution among all periods. To consider the accident loss, for each route, two essential parameters are estimated based on historical data; the occurrence probability and severity index of accident. The model therefore attempts to utilize the best configuration of the routes and transshipment option to satisfy the demand while minimizing the costs and accident loss simultaneously. Several numerical examples are generated and solved by CPLEX and compared with the solutions of an efficient Hybrid Genetic Algorithm (HGA). The results show that the transshipment option not only can be used as a lever to increase the economic supply network performance through saving the routes, but also it can help the system to avoid risky routes.

An insight into centralised sourcing strategy for enhancing performance and sustainability of multi-tier supply network

In a multi-tier supply network, sourcing strategy, consisting of supplier selection (SS) and order quantity allocation (OQA) to selected supplier(s), is a critical and challenging task for practitioners. Every player, in every tier of sourcing network, attempts to select quality conscious suppliers and optimise its own inventory cost per unit time for OQA. However, this may results in sub-optimal solution(s) for overall multi-tier supply network. Considering centralised sourcing strategy for SS and OQA may provide global best solution and sustainable supply network. This paper attempts to quantitatively illustrate inventory cost saving for coordinated centralised sourcing strategy for all tiers compared to independent decentralised sourcing strategy at individual tier in the supply network. Suitable mathematical models (single and multi-tier) and corresponding solution framework is used to determine local optima and global best solution for a comparative analysis. A real life electric goods manufacturing industry case study is used to demonstrate significant cost advantage for a centralised as compared to decentralised sourcing strategy. Sensitivity analysis with varied unit material price is also illustrated in this study.

An insight into centralised sourcing strategy for enhancing performance and sustainability of multi-tier supply network

In a multi-tier supply network, sourcing strategy, consisting of supplier selection (SS) and order quantity allocation (OQA) to selected supplier(s), is a critical and challenging task for practitioners. Every player, in every tier of sourcing network, attempts to select quality conscious suppliers and optimise its own inventory cost per unit time for OQA. However, this may results in sub-optimal solution(s) for overall multi-tier supply network. Considering centralised sourcing strategy for SS and OQA may provide global best solution and sustainable supply network. This paper attempts to quantitatively illustrate inventory cost saving for coordinated centralised sourcing strategy for all tiers compared to independent decentralised sourcing strategy at individual tier in the supply network. Suitable mathematical models (single and multi-tier) and corresponding solution framework is used to determine local optima and global best solution for a comparative analysis. A real life electric goods manufacturing industry case study is used to demonstrate significant cost advantage for a centralised as compared to decentralised sourcing strategy. Sensitivity analysis with varied unit material price is also illustrated in this study.

A supply network governance framework: a case study of the South Australian mining industry

Purpose The competitiveness of mining regions largely depends on the performance of the regional supply chains that provide services to mining companies. These local supply chains are often highly intertwined and represent a regional supply network for the industry. Individual companies often use supply chain strategies that are sub-optimal to overall supply network performance. To effectively respond to an uncertain business environment, policy-makers and supply chain participants would benefit by a governance framework that would allow to incentivise the formation of supply networks structures enabling effective operations. The purpose of this paper is to offer an empirically grounded conceptual framework based on Complex Adaptive Systems (CASs) governance principles, which links network governance mechanisms with supply network structure and operational performance to incentivise the formation of adaptive and resilient supply networks in the mining industry. Design/methodology/approach A mixed method research design and a case study of the South Australian mining sector were used to collect empirical data. Qualitative interviews and network analysis of the SA mining industry regional supply network structure were conducted. The relationships between network parameters were interpreted using CAS theory. Findings An empirically grounded conceptual framework based on CAS governance principles is developed. The case study revealed that supply chain strategies and governance mechanisms in the SA mining industry have led to the formation of a hierarchical, scale-free structure with insufficient horizontal connectivity which limits the adaptability, responsiveness and resilience of the regional supply network. Research limitations/implications The findings are drawn from a single case study. This limits generalisability of the findings and the proposed framework. Practical implications The proposed framework draws the attention of the policy-makers and supply chain participants towards the need for utilising CAS governance principles to facilitate the formation of adaptive, responsive and resilient regional supply networks in the mining industry. Originality value The proposed conceptual framework is an attempt to parameterise the governance of the regional supply networks in the mining industry.

The Impact of Control and Complexity on Supply Network Performance: An Empirically Informed Investigation Using NK Simulation Analysis

ABSTRACTControl over suppliers is a core issue for a buying firm. Despite the amount of research on the topic, how much of its supply network (i.e., scope of control) a buying firm should control, so as to increase supply network performance, is a question that has not received adequate research attention. The study addresses this research question by considering the supply network as a complex adaptive system and developing an empirically informed agent‐based simulation model using the NK fitness landscape framework, to examine how varying levels of scope of control influence supply network performance. We also investigate the direct effect of two supply network complexity dimensions (i.e., number of firms and level of supply interactions) on supply network performance and the moderating effect played by the scope of control. Results show that the relationship between scope of control and supply network performance follows an inverted‐U shape. Furthermore, we find that the complexity dimensions negatively affect supply network performance with the performance decrease depending on the scope of control. Based on these findings, we formulate different control strategies to mitigate the negative influence of complexity.

Optimizing decisions in advanced manufacturing of prefabricated products: Theorizing supply chain configurations in off-site construction

Abstract Robust supply decision making is critical to the advanced manufacturing of prefabricated products. Previous related research focused on minimizing cost overruns in off-site construction supply networks by optimizing purchasing decisions. However, decision parameters such as strategic preferences to include or exclude certain suppliers and utilization of multi-supplier configurations are yet to be formulated and analytically solved. The proposed optimization models aim to enhance supply network performance with a smaller overall investment. Toward this aim, three research hypotheses on optimization of supply decisions and configurations are developed and tested. A real-world precast panel production project serves as the test bed to demonstrate the effectiveness of the mathematical programming and analyze cost implications of supply related decisions. The modeling method and results contribute to optimal decision making in advanced manufacturing of prefabricated products.

Sustainable network design for multi-purpose pellet processing depots under biomass supply uncertainty

This study develops a two-stage stochastic mixed-integer programming model to manage multi-purpose pellet processing depots under feedstock supply uncertainty. The proposed optimization model would help to minimize cost and mitigate emissions from the supply chain network. We consider three alternative Biomass Processing and Densification Depot (BPDD) technologies; namely, conventional pellet processing, high moisture pellet processing, and ammonia fiber expansion. These three technologies pre-process/pre-treat and densify different types of biomass into more highly densified intermediate products for different markets in order to improve movability and overall supply network performance in terms of costs and emissions. A hybrid decomposition algorithm was developed that combines Sample Average Approximation with an enhanced Progressive Hedging (PH) algorithm to solve this challenging NP-hard problem. Some heuristics such as Rolling Horizon (RH) heuristic, variable fixing technique were later applied to further enhance the PH algorithm. Mississippi and Alabama were selected as a testing ground and ArcGIS was employed to visualize and validate the modeling results. The results of the analysis reveal promising insights that could lead to recommendations to help decision makers achieve a more cost-effective environmentally-friendly supply chain network.

Medición del desempeño de la red de suministros de medicamentos en un hospital público de tercer nivel en la ciudad de Bogotá, a través del cuadro de mando integral


 
 
 
 
 
 
 
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 Inicio > Núm. 20 (2016) > Arciniégas C
 
 
 
 Medición del desempeño de la red de suministros de medicamentos en un hospital público de tercer nivel en la ciudad de Bogotá, a través del cuadro de mando integral
 
 Luis C. Arciniégas C, Manuel Á. Camacho O, Manuel Á. Camacho O, Edgar L. Duarte F, Edgar L. Duarte F, Alexander Naranjo L, Alexander Naranjo L
 
 
 Resumen
 
 
 El artículo contribuye al conocimiento de la medición del desempeño de la red de suministro en el marco de la logística hospitalaria a partir de la aplicación del Cuadro de Mando Integral (CMI). Como objetivo general se plantea el desarrollo de una metodología para la medición del desempeño de la red de abastecimiento de medi-camentos en el Hospital Universitario de La Samaritana (HUS), de manera que se mejore el proceso de toma de decisiones dentro de la organización. El proceso metodológico aplicado consta de tres etapas: caracterización del flujo de medicamentos en el HUS; identificación de las variables relevantes en el proceso de medición e implementación del esquema de medición, y finalmente el análisis de los datos recolectados para la medición del sistema logístico. Como resultado de este proceso se obtuvieron los indicadores claves de desempeño de la red de suministro de medicamentos y de manera particular se propone un método de medición bajo un índice único normalizado. Se concluye que la aplicación de un índice único normalizado facilita los procesos de análisis de información, de igual forma se resalta la versatilidad de la metodología CMI en el análisis del desempeño de la red de suministros en el hospital.