Wafa Alalaween

University of Jordan | UJ · Department of Industrial Engineering

Due to the global COVID-19 pandemic, governments have adopted regulations and restrictions to prevent spreading the disease. Changes in socioeconomic status, lifestyle, mobility and consumer consumption behavior have resulted due to these restrictions. These changes caused the amount and pattern of electricity consumption to be affected during and...

Right-first-time production enables manufacturing companies to be profitable as well as competitive. Ascertaining such a concept is not as straightforward as it may seem in many industries, including 3D printing. Therefore, in this research paper, a right-first-time framework based on the integration of fuzzy logic and multi-objective swarm optimiz...

The Ball Clamping module of the Laparoscopic Surgery Training Box involves the transfer of beads across the training board using laparoscopic tools. Fundamentals of Laparoscopic Surgery (FLS) requires practitioners to move their hands at as short a distance as possible to perform the functions in the shortest amount of time. This study introduces a...

Lean implementation in the service sector has a dilemma related to defining the gap of the lean system and identifying the flaws in the processes which affect the overall performance and efficiency. This paper presents an innovative model that can help service companies to improve lean implementation and integrate appropriate Key Performance Indica...

Purpose The purpose of this research paper is to investigate and model the fused deposition modelling (FDM) process to predict the mechanical attributes of 3D printed specimens. Design/methodology/approach By exploiting the main effect plots, a Taguchi L18 orthogonal array is used to investigate the effects of such parameters on three mechanical a...

The turning process is considered to be one of the most important machining processes. The various combinations of the input parameters can indeed determine the fate of the quality of the produced parts. This study aims to investigate the effect of various combinations of the input parameters on the surface roughness and the force required in order...

The hybrid electric vehicles (HEVs) market has grown tremendously in the past few years which, as a result, has led to an exponential growth in the spare parts (SPs) market. Therefore, there is a strong need, nowadays, to predict the demand as well as the price of these SPs. However, ascertaining such an aim is not as easy as it may seem, this bein...

This research presents a compensated fuzzy logic system that integrates an interval type-2 fuzzy logic system (IT2FLS) with the Gaussian mixture model (GMM) to model the turning process. First, an IT2FLS is elicited to model the turning process by mapping its input variables to the cutting force and the surface quality. Second, the GMM is incorpora...

Coronavirus (COVID-19) has captured the attention of the globe very rapidly. Therefore, predicting the spread of the disease has become an indispensable process, this is being due to its extremely infectious nature and due to the negative effects that some courses of actions, which were taken to minimize the spread of the disease, have on economy a...

A new integrated assessment algorithm is proposed for a warehouse assessment scheme. This new algorithm integrates three paradigms, namely, Grey Relational Analysis (GRA), Data Envelopment Analysis (DEA), and an Interval Type-2 Fuzzy Logic System (IT2FLS). Based on the defined criteria and the various warehouses assessed according to these criteria...

A novel way of integrating the genetic algorithm (GA) and the analytic network process (ANP) is presented in this paper in order to develop a new warehouse assessment scheme, which is developed through various stages. First, we define the main criteria that influence a warehouse performance. The proposed algorithm that integrates the GA with the AN...

A new integrated modelling architecture based on the concept of the fuzzy logic is presented to represent the turning process. Such an architecture consists of two stages. In the first stage, fuzzy logic systems (FLSs) having various topologies are employed to extract rule bases using perhaps limited amount of sparse data. In the second stage, the...

A new dynamic assessment algorithm based on the Type-1 Fuzzy Logic System (T1FLS) is proposed in this research work to develop a dynamic warehouse assessment scheme. First, the criteria and the sub-criteria that affect a warehouse performance are identified and, then, classified into a number of clusters. Second, the warehouse performance score is...

Medical devices used in healthcare organizations are costly, and the process of selecting these devices requires considering multiple criteria such as effectiveness and ease of use. Careful selection of these devices is daunting since it entails the evaluation of various measures. This research investigates the selection process of the same type of...

Purpose These days vehicles' spare parts (SPs) are a very big market, and there is a very high demand for these parts. Forecasting vehicles' SPs price and demand are difficult because of the lack of data and the pricing of the SPs is not following the normal value chain methods like normal products. Design/methodology/approach A proposed model usi...

The concept of right-first-time production is an essential feature for a successful product development process and for companies to be competitive and profitable. However, achieving such a concept is a tricky exercise across a wide spectrum of industrial domains includes the pharmaceutical industry where granulation and tableting processes are con...

In this research, a new framework based on fuzzy logic is proposed to model the twin screw granulation (TSG) process. First, various fuzzy logic systems (FLSs) having different structures are developed to define various rule bases. The extracted fuzzy rules are assessed and reduced accordingly into a single rule base by utilizing the singular value...

This study presents a modelling framework to predict the flowability of various commonly used pharmaceutical powders and their blends. The flowability models were trained and validated on 86 samples including single components and binary mixtures. Two modelling paradigms based on artificial intelligence (AI) namely, a radial basis function (RBF) an...

In this research, a new systematic modelling framework which uses machine learning for describing the granulation process is presented. First, an interval type-2 fuzzy model is elicited in order to predict the properties of the granules produced by twin screw granulation (TSG) in the pharmaceutical industry. Second, a Gaussian mixture model (GMM) i...

A hybrid model based on physical and data interpretations to investigate the high shear granulation (HSG) process is proposed. This model integrates three separate component models, namely, a computational fluid dynamics model, a population balance model, and a radial basis function model, through an iterative procedure. The proposed hybrid model i...

The granulation process is considered to be a crucial operation in many industrial applications. The modelling of the granulation process is, therefore, an important step towards controlling and optimizing the downstream processes, and ensuring optimal product quality. In this research paper, a new integrated network based on Artificial Intelligenc...

Today’s complexity of product design requires improving multiple quality characteristics. This research proposes an approach that integrates the desirability function and data envelopment analysis to enhance process performance with dynamic multi-responses. Firstly, the desirability function is employed. Then, data envelopment analysis is used to o...