MULTI-OBJECTIVE OPTIMIZATION MODELING OF INTEGRATED SUPPLY CHAIN FOR SOLID WASTE TREATMENT

Solid waste management (SWM) has been proven as a vital research area, as it contributes in providing a basic and renewal source of production resources like recycled raw materials, fuel and energy sources. Hence, this research investigates the SWM problem by simultaneous consideration of key environmental and economic factors. In this regard, a multi-objective mathematical model is presented for an integrated solid waste supply chain to minimize total costs and environmental impacts while maximizing the recovered energy. The designed supply chain is being modeled as a weighted goal programming (WGP) model to achieve the desired objectives, and this model is solved by applying a simplex-based solution algorithm. In addition, the model and the solution algorithm are validated through the application on real case study data. The comparisons’ results show that the integrated supply chain’s model attains reasonably outperforming results in terms of minimizing the average total cost and environmental impacts

Blockchain for Healthcare Systems: Concepts, Applications, Challenges, and Future Trends

-Electronic medical records are digital documents that contain medical data pertaining to a patient\u27s medical care. Because electronic health records are regularly exchanged amongst stakeholders in healthcare, they are prone to a range of challenges such as data misuse and loss of privacy and security. These challenges may be solved by utilizing blockchain-based technologies in the healthcare area. Blockchain is a decentralized innovative technology that can completely transform, reshape, and reinvent how data is stored and processed in the healthcare sector. In this article, we offer an overview of the blockchain, its formation, its types, and how it works. We review the various applications of blockchain in the medical field and how Blockchain revolutionized the medical industry. We highlight previous scientific research on the application of blockchain to electronic health record systems (EHRs). Finally, we discuss the open research problems that limit the use of blockchain in the medical field

Comparison and Evaluation of Deadlock Prevention Methods for Different Size Automated Manufacturing Systems

In automated manufacturing systems (AMSs), deadlocks problems can arise due to limited shared resources. Petri nets are an effective tool to prevent deadlocks in AMSs. In this paper, a simulation based on existing deadlock prevention policies and different Petri net models are considered to explore whether a permissive liveness-enforcing Petri net supervisor can provide better time performance. The work of simulation is implemented as follows. (1) Assign the time to the controlled Petri net models, which leads to timed Petri nets. (2) Build the Petri net model using MATLAB software. (3) Run and simulate the model, and simulation results are analyzed to determine which existing policies are suitable for different systems. Siphons and iterative methods are used for deadlocks prevention. Finally, the computational results show that the selected deadlock policies may not imply high resource utilization and plant productivity, which have been shown theoretically in previous publications. However, for all selected AMSs, the iterative methods always lead to structurally and computationally complex liveness-enforcing net supervisors compared to the siphons methods. Moreover, they can provide better behavioral permissiveness than siphons methods for small systems. For large systems, a strict minimal siphon method leads to better behavioral permissiveness than the other methods

Experimental Investigations on Dry Sliding Wear Behavior of Kevlar and Natural Fiber-Reinforced Hybrid Composites through an RSM–GRA Hybrid Approach

The present work aimed to investigate the dry sliding wear behaviors of hybrid polymer matrix composites made up of Kevlar, bamboo, palm, and Aloe vera as reinforcement materials of varying stacking sequences, along with epoxy as the matrix material. Three combinations of composite laminates with different stacking sequences such as AB, BC, and CA were fabricated by a vacuum-assisted compression molding process. The influence of composite laminates fabricated through various stacking sequences and dry sliding wear test variables such as load, sliding distance, and sliding velocity on the specific wear rate and co-efficient of friction were investigated. Experiments were designed and statistical validation was performed through response surface methodology-based D-optimal design and analysis of variance. The optimization was performed using grey relational analysis (GRA) to identify the optimal parameters to enhance the wear resistance of hybrid polymer composites under dry sliding conditions. The optimal parameters, such as composite combinations of CA, a load of 5 N, a sliding velocity of 3 m/s, and a sliding distance of 1500 m, were obtained. Furthermore, the morphologies of worn-out surfaces were investigated using SEM analysis

Sustainable design of self-consolidating green concrete with partial replacements for cement through neural-network and fuzzy technique

In order to achieve a sustainable mix design, this paper evaluates self-consolidating green concrete (SCGC) properties by experimental tests and then examines the design parameters with an artificial intelligence technique. In this regard, cement was partially replaced in different contents with granulated blast furnace slag (GBFS) powder, volcanic powder, fly ash, and micro-silica. Moreover, fresh and hardened properties tests were performed on the specimens. Finally, an adaptive neuro-fuzzy inference system (ANFIS) was developed to identify the influencing parameters on the compressive strength of the specimens. For this purpose, seven ANFIS models evaluated the input parameters separately, and in terms of optimization, twenty-one models were assigned to different combinations of inputs. Experimental results were reported and discussed completely, where furnace slag represented the most effect on the hardened properties in binary mixes, and volcanic powder played an effective role in slump retention among other cement replacements. However, the combination of micro-silica and volcanic powder as a ternary mix design successfully achieved the most improvement compared to other mix designs. Furthermore, ANFIS results showed that binder content has the highest governing parameters in terms of the strength of SCGC. Finally, when compared with other additive powders, the combination of micro-silica with volcanic powder provided the most strength, which has also been verified and reported by the test results

Confusion Control in Generalized Petri Nets Using Synchronized Events

The loss of conflicting information in a Petri net (PN), usually called confusions, leads to incomplete and faulty system behavior. Confusions, as an unfortunate phenomenon in discrete event systems modeled with Petri nets, are caused by the frequent interlacement of conflicting and concurrent transitions. In this paper, confusions are defined and investigated in bounded generalized PNs. A reasonable control strategy for conflicts and confusions in a PN is formulated by proposing elementary conflict resolution sequences (ECRSs) and a class of local synchronized Petri nets (LSPNs). Two control algorithms are reported to control the appeared confusions by generating a series of external events. Finally, an example of confusion analysis and control in an automated manufacturing system is presented

Role of evolutionary epidemiology in the determination of the risk factors associated with some equine viral diseases

The evolutionary epidemiology is crucial as it does not only help in tracking the origin, spreading, prediction, and control of viruses but also explains the failure causes of some vaccines and serological diagnostic tools. To keep animal welfare, it is essential to raise awareness of the multiple risk factors associated with the different epidemics. Arthropod-borne viruses like African horse sickness virus (AHSV) and equine infectious anaemia virus (EIAV) are related to vectors multiplication. Accordingly, their seasonal occurrence was attributed to the environmental climatic conditions. While equine influenza virus (EIV) and equine herpes virus (EHV) were found to occur in winter and spring (foaling seasons), respectively. The management risk factors resulted in the occurrence and reactivation of latently infected cases. The RNA viruses are characterized by genetic assortment which results in increasing pathogenicity, and failure of the used vaccines. The EHVs able to establish infection in different host tissues adding to their immune evasion strategies. Most of the diseases occurred at the age over 2 years although the EIAV takes long time to appear. The hard work of males and other stress factors render them more liable for infection with equine viral arteritis (EVA), EIAV, and EHV. Genetically, some breeds of horses were at risk of AHSV, EVA, and EHV infection. Most of the donkeys, mules, and zebra develop subclinical forms that magnifies their role in the epidemiological situation. Different phenomena like overwintering in AHSV, hard work in EIV, virus hidden nature and latency in EHV should be more analysed

A Model for Maintenance Planning and Process Quality Control Optimization Based on EWMA and CUSUM Control Charts

The performance of a production system is highly dependent on the smooth operation of various equipment and processes. Thus, reducing failures of the equipment and processes in a cost-effective manner improves overall performance; this is often achieved by carrying out maintenance and quality control policies. In this study, an integrated optimization method that addresses both maintenance strategies and quality control practices is proposed using an exponentially weighted moving average (EWMA) chart, in which both corrective and preventive maintenance policies are considered. The integrated model has been proposed to find optimal decision variables of both the process quality decision parameters and the optimal interval of preventive maintenance (i.e., Ns, Hs, L, λ, and t_PM) to result in overall optimal expected hourly total system costs. A case study is then utilized to investigate the impact of cost criteria on the proposed integrated model and to compare the proposed model with a model using the cumulative sum (CUSUM) control chart. The improved model outputs indicate that there is a reduction of 34.6% in the total expected costs compared with those of the other model using the CUSUM chart. Finally, an analysis of sensitivity to present the effectiveness of the model parameters and the main variables in the overall costs of the system is provided

A New Association Analysis-Based Method for Enhancing Maintenance and Repair in Manufacturing

Maintenance and quality of products are absolutely crucial for any organization to succeed in the industrial and manufacturing engineering. Current research studies have confirmed the presence of a high correlation between these two factors, namely maintenance and quality of products, in industrial organizations. Nevertheless, no extensive research has been conducted in order to study the link between maintenance and the quality of products in manufacturing. In this paper, we conduct a study in this domain and examine the relationship patterns between maintenance and the quality of product using manufacturing data on maintenance and the product quality. Specifically, we employ association analysis and association rule mining with large and extensive sets of product quality, repair, and maintenance data. Our main objective is to discover interesting and non-trivial associations for feature failure resulting in the repair or maintenance of a product with unapproved quality. The results of evaluation are quite interesting. The resulting association rules with high values of confidence and lift suggest some essential associations between the product features and the failure; such findings have not been known and used before. This can help quality engineers and maintenance teams to enhance maintenance and repair operations and lower the overall cost of manufacturing