WSN based intelligent cold chain management

This paper presents a cold chain monitoring system which is implemented by using ubiquitous computing technologies, Radio Frequency Identification (RFID) & Wireless Sensor Network (WSN). In this paper, we discuss how cold supply chain works and how we can monitor and control cold supply chain by using wireless tracking and sensing technologies. We propose a prototype design which will provide a well controlled and transparent cold chain system, which could help the users to manage their products’ environmental data in real time during the life cycle. Moreover, we highlight how the availability of product trace data in combination with historical condition-monitoring data can facilitate decision-making processes enhancing supply chain’s performance. Finally we discuss the integration works of these two technologies together in the cold supply chain management system. Hardware and software platform of WSN used in this system are also described in this paper

Revolutionizing Pharmaceutical Cold Chain Competency Framework with Reference Process Model and Reference Architecture

The utilization of the reference process model (RPM) and reference architecture (RA) as disruptive information and communication technologies (ICT) in the pharmaceutical cold chain (PCC) industry has enabled the management of tasks through a model-architecture-based approach. This research presents an innovative method for competency development in the cold chain sector, leveraging RPM and RA. By introducing a comprehensive conceptual framework encompassing RPM and RA design and workflow into cold chain competency development, this study outlines the key areas for incorporating RPM and RA into the PCC field. The framework elucidates the functioning of RPM and RA concerning occupational standards (OS) and units of competencies (UOC) within the industry. The study generates a research framework for the PCC industry by systematically implementing RPM and RA using a proposed method. The primary outcomes and empirical evidence are UOC and OS derived from RPM and RA implementation and integration, substantiating the conceptual framework's validity. The research highlights the evolutionary aspects and the significance of the conceptual framework in guiding the research framework and proposes a method for competency development. Furthermore, recommendations are provided for future research endeavors. Doi: 10.28991/HIJ-2023-04-02-011 Full Text: PD

Energy Management of Context-aware Cold Chain Vehicle Nodes

In view of the question that the energy-constrained sensor nodes affect the normal operation of the whole system due to the short survival period, in this paper we present a new solution of adaptive energy management from the angle of context-aware computing. In different scenario modes, we take different environment acquisition and communication strategy according to scenario parameters, and thus build the context-aware energy management model. Finally, we extend the whole system life by lowering energy consumption of single internet of things vehicle node. Experimental data show that the energy management plan of context-aware wireless sensor nodes effectively reduces the energy consumption of nodes and extends the system life under the premise of providing reliable services

Using real-time truck transportation information to predict customer rejections and refrigeration-system fuel efficiency in packaged salad distribution

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 139-141).Companies that operate cold supply chains can greatly benefit from information availability and data generation. The abundance of information now available to cold chain operators and harvested from every echelon of the supply chain, ranging from the procurement process to the sales and customer service processes, provides an opportunity for logistics organizations to monitor and improve their operations. It is increasingly imperative to transform data into meaningful information that creates a competitive advantage for early adopters. This thesis attempts to determine how to make best use of and effectively interpret the information generated by trailer mounted temperature sensors and geospatial data collection devices during refrigerated transportation of packaged salads. The study covers only the transportation segment from the manufacturer's distribution center to the customer's (grocery retailer) distribution center. This thesis uses regression analysis in an effort to create a model that effectively uses realtime transportation information to identify the elements that can create a competitive advantage for cold chain operators. The main performance measurements subject to analysis in this thesis are reefer-unit fuel consumption and rejections of salad products at the customer's drop location. Regression yields a formula that can predict more than 70% reefer fuel consumption. However, with the independent variables available in the data at our disposal, it is not possible to build a model the effectively predicts product rejections. The findings of this thesis can help operators of transportation cold chains better manage fuel consumption by isolating and improving the independent variables we identified.by Carlos Seminario and Emmanuel Marks.M.Eng.in Logistic

The Value of RFID Technology Enabled Information to Manage Perishables

We address the value of RFID technology enabled information to manage perishables in the context of a supplier that sells a random lifetime product subject to stochastic demand and lost sales. The product's lifetime is largely determined by the time and temperature history in the supply chain. We compare two information cases to a Base case in which the product's time and temperature history is unknown and therefore its shelf life is uncertain. In the first information case, the time and temperature history is known and therefore the remaining shelf life is also known at the time of receipt. The second information case builds on the first case such that the supplier now has visibility up the supply chain to know the remaining shelf life of inventory available for replenishment. We formulate these three different cases as Markov decision processes, introduce well performing heuristics of more practical relevance, and evaluate the value of information through an extensive simulation using representative, real world supply chain parameters.simulation;value of information;RFID;perishable inventory

Modeling Psychrometric Data in Real-Time Fruit Logistics Monitoring

Progress in fruit logistics requires an increasing number of measurements to be performed in refrigerated chambers and during transport. Fruits and vegetables are submitted to a variety of risks during transport and storage that are responsible for material quality losses. Among them water loss and condensation are causes of deterioration that reduces the marketability of fresh fruits and vegetables. Wireless sensor networks (WSN) are a promising solution in monitoring food logistics. Instrumented with sensors, such as temperature and humidity, this technology allows on-line supply chain monitoring of perishable food products. Psychrometry studies the thermodynamic properties of moist air and the use of these properties to analyze conditions and processes involving moist air. Using the information provided by the sensors, psychrometric equations can be used for quick assessment of changes in the absolute water content of air, allowing estimation of future water loss and detection of condensation. In this paper the psychrometric data from ASABE (American Society of Agricultural and Biological Engineers) has been applied, for modeling evaporation and condensation of water related with regard to product in a refrigerated chamber. The experiments were conducted in a commercial wholesaler store in the fruit and vegetables wholesalers market of Madrid. Two different types of IEEE 802.15.4/ ZigBee motes have been used

Identification of the critical enablers for perishable food supply chain using deterministic assessment models

Today’s perishable food supply chains must be resilient to handle volatile demands, environmental restrictions, and disruptions in order to meet customers’ requirements. The enablers of the perishable food supply chain have not yet been explored. In this paper, a bibliometric systematic literature review has been conducted to identify the articles related to the perishable food supply chain. Next, with these identified articles, a map is created with bibliographic data using Vosviewer network visualization software, and then the enablers were identified by conducting keyword co-occurrence analysis. Later, a total interpretive structural modeling (TISM) is employed to analyze the interrelationships among enablers and then determine each enabler’s hierarchies, further representing them in a diagraph. Finally, the identified enablers are classified using cross-impact matrix multiplication applied to classification (MICMAC) analysis, and the graph is plotted. The results obtained from the deterministic assessment model provide the critical enablers for the perishable food supply chain. The obtained critical enablers and their hierarchies provide valuable insights for researchers in the context of perishable food supply chain for further study.The authors are grateful to FCT - Fundação para a Ciência e Tecnologia who financially supported this work through the RD Units Project Scope: UIDP/04077/2020 and UIDB/04077/2020