Leveraging on the Digital Twin for improving retail store daily operations management

With the fast development of IoT technologies and the potential of real-time data gathering, allowing decision makers to take advantage of real-time visibility on their processes, the rise of Digital Twins (DT) has attracted several research interests. DT are among the highest technological trends for the near future and their evolution is expected to transform the face of several industries and applications and opens the door to a huge number of possibilities. However, DT concept application remains at a cradle stage and it is mainly restricted to the manufacturing sector. In fact, its true potential will be revealed in many other sectors. In this research paper, we aim to propose a DT prototype for instore daily operations management and test its impact on daily operations management performances. More specifically, for this specific research work, we focus the impact analysis of DT in the fitting rooms’ area.

Simulation model of supply networks development

The paper is dedicated to network development in the network economy. The current economy needs to look not only at networks with only dynamic flows and with a fixed structure, but as a dynamic system its structure evolves and changes. Structure and behaviour dynamics of network systems can be modelled as complex adaptive systems and use agent-oriented simulation to demonstrate origin, perturbation effects, and sensitivity with regard to initial conditions. Survival of firms is associated with the value of so-called fitness function. Firms whose fitness value falls below a certain threshold will be extinguished. In this way, it is possible to partially model network growth. A simulation model in SIMUL8 is proposed.

Integration of process mining techniques in simulation results analysis

The research is carried out in the area of analysis of simulation results. The aim of this research is to explore the applicability of process mining techniques, and to introduce the process mining techniques integration into results analysis of discrete-event system simulations. As soon as the dynamic discrete-event system simulation (DESS) is based on events list or calendar, most of simulators provide the events lists. These events lists are interpreted as event logs in this research, and are used for process mining. The information from the events list is analysed to extract process-related information and perform in-depth process analysis. Event log analysis verified applicability of the proposed approach. Based on the results of this research, it can be concluded that process mining techniques in simulation results analysis provide a possibility to reveal new knowledge about the performance of the system, and to find the parameter values providing the advisable performance.

Appraisal of OFDM for multi-carrier, high-speed data rate wireless communication networks

Orthogonal Frequency Division Multiplexing (OFDM) is used to achieve multi-carrier signals and high- Speed data rate in free space. OFDM-based systems operate in the hostile multipath radio environment, which allows efficient sharing of limited resources. This research work was designed, developed and simulated an OFDM System using the basic blocks of Simulink in MATLAB/Simulink software, to support multi-carrier, high-speed data rates. This was achieved in backing of collection and review of high-quality research papers, which reported the latest research developments in OFDM communications networks, and its applications in future wireless systems. The research work significantly increases the speed of data rate signals, and many critical problems associated with the applications of OFDM technologies in future wireless systems are still looking for efficient solutions. This would overcome the global issues and challenges facing the limited bandwidth in wireless communication network.

Fuel-optimal path finding algorithm using traffic information at urban intersection

Intelligent Transportation System (ITS) is actively studied as the sensor and communication technology in the vehicle develops. The Intelligent Transportation System collects, processes, and provides information on the location, speed, and acceleration of the vehicles in the intersection. This paper proposes a fuel optimal route decision algorithm. The algorithm estimates traffic condition using information of vehicles acquired from several ITS intersections and determines the route that minimizes fuel consumption by reflecting the estimated traffic condition. Simplified fuel consumption models and road information (speed limit, average speed, etc.) are used to estimate the amount of fuel consumed when passing through the road. Dynamic Programming (DP) is used to determine the route that fuel consumption can be minimized. This algorithm has been verified in an intersection traffic model that reflects the actual traffic environment (Korea Daegu Technopolis) and the corresponding traffic model is modeled using AIMSUN.

Wearable Mixed Reality Solutions for Industrial Plants and Production Lines

"In the present research project, the authors developed wearable and portable solutions capable to improve safety in production lines by taking advantages of availability of exhaustive and reliable data in modern industrial plants. Indeed, the synergy between Industry 4.0 and cutting edge devices, such as smartphones and headsets for Mixed Reality demonstrated to be potentially used to assist personnel on the shop floor, especially during critical and most dangerous operations. In this paper it is presented an ongoing project devoted to develop such support systems and to evaluate their efficiency in multiple industrial environments."

Optimal hybrid drive system architecture exploration considering performance index of 48V mild HEV

The 48V hybrid system has mostly adopted parallel hybrid system architecture. In the parallel hybrid system, various architecture can be derived depending on the location of the motor. In this paper, we explored a hybrid system architecture considering one or two motors and 48V electric supercharger and derived the optimal architecture by comparing the performance of each architecture. Performance of the hybrid system is mostly evaluated as fuel economy. However, since the hybrid system has increasingly been applied to various types of vehicles with different purpose of the operation, another performance index for evaluating a hybrid system is needed. Therefore, in this paper, we introduced an additional performance index to evaluate the hybrid electric drive system and used it to derive the optimal architecture of the hybrid electric drive system. We used Dynamic programming (DP) to evaluate each architecture and DP simulation was performed in the Matlab environment.

A simulation tool for mass transfer inside compressed air vessel for water networks pressurisation

Feeding a water distribution network with the correct pressure is a fundamental requirement for its proper operation; to this end, a simple and reliable solution commonly adopted in small and medium industrial plants is the adoption of a pressure vessel. For small systems, a membrane seals the system water from the gas compartment, anyway, as the size of the vessel increases, the adoption of sealing diaphragm or bladder is no longer feasible, and thus there is a direct contact between air and water. The high pressure of the vessel, combined with the cyclic loading and unloading phases, which replace the water inside the tank, leads to a considerable mass transfer phenomenon of air inside water. The loss of air mass cannot be monitored and detected by simply controlling system pressures; to this extent, water level measurement and reference analytical models are required. Since there is a lack in scientific literature of these models, the present study presents a model for mass transfer estimate in the systems described, starting from a real pilot plant. The main results of the model implementation in a spreadsheet, in terms of the trend of the key model parameters in time, are also reported and discussed.

Nonparametric frequency polygon estimation for modeling input data

To construct valid probability distributions solely from input data, this paper compares three nonparametric density estimators: (1) histograms, (2) Kernel Density Estimation, and (3) Frequency Polygon Estimation. A pseudocode is implemented, a practical example is illustrated, and the Simphony.NET simulation environment is used to fit the nonparametric frequency polygon to a set of data to recreate it as a posterior distribution via the Metropolis-Hastings algorithm.

Machine learning techniques applied to industrial engineering: a multi criteria approach

With the Industry 4.0 (I4.0) beginning, the world is witnessing an important technological development. The success of I4.0 is linked to the implementation of enabling technologies, including Machine Learning, which focuses on the machines’ ability to receive a series of data and learn on their own. The present research aims to systematically analyze the existing literature on the subject in various aspects, including publication year, authors, scientific sector, country, institution and keywords. Understanding and analyzing the existing literature on Machine Learning applied to predictive maintenance is preparatory to recommend policy on the subject.