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

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

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

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

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

Parametric optimization of wear parameters of hybrid composites (LM6/B4C/fly ash) using Taguchi technique

Wear is prominent in sliding components, so tribology property plays a major role in automotive as well as in the aerospace industries. In this work, Aluminium alloy LM6/B4C/Fly Ash hybrid composites with three different weight percentages of reinforcement were fabricated using the low-cost stir casting technique, and the experiments were conducted based on the Design of Experiments (DoE) approach and optimized using Taguchi’s Signal to noise ratio (S/N) analysis. The analysis was conducted with process parameters like Sliding Speed (S), Sliding distance (D), load (L) and reinforcement percentage (R %), the responses are Coefficient of Friction (COF) and Specific wear rate (SWR). Aluminum alloy reinforced with 9 wt% hybrid (LM6 + 4.5% B4C + 4.5% Fly Ash) has a low density and high hardness compared with other composites and base alloys. The optimum parameters for obtaining minimum SWR are S - 1 m/s, D - 500 m, L - 45 N, and R% - 6 wt% Hybrid (3% Fly ash and 3% boron carbide). The optimum parameters for obtaining minimum COF are S - 1.5 m/s, D - 500 m, L - 30 N, and R% −9 wt% Hybrid (4.5% Fly ash and 4.5% boron carbide). Load (28.34%) is the most significant parameter for obtaining minimum SWR, and DL (31.62%) for obtaining minimum COF. SEM images of the worn pins show the various wear mechanisms of the AMCs. The hybrid composite produced is new and these may be used for piston liner and brake pad applications

[In Press] Efficient machine-learning algorithm applied to predict the transient shock reaction of the elastic structure partially rested on the viscoelastic substrate

Due to numerous applications of piezoelectric materials in the modern technologies, this study assesses the thermomechanical shock behavior of the functionally graded graphene platelets reinforced nanocomposite (FG-GPLRN) annular plate surrounded by two piezoelectric layers and partially rested on the viscoelastic substrate for different cases of boundary conditions by metaheuristic optimized machine-learning methods, for the first time. Thermal and mechanical shocks are simultaneously applied on the upper surface of the mentioned structure. Governing equations of the system are formulated in the background of three-dimensional (3D) elasticity theory. Energy balance of the system is considered based on the Lord-Shulman theorem. Differential quadrature method (DQM) is selected as the main solver to determine the spatial response of the system from the state-space form of the governing differential equations. Additionally, Laplace transform is collaborated with modified Dubner and Abate’s approach to predict the temporal response of the system. Accuracy of the applied methods is carefully examined and verified through comparative study performed between the current results and those determined in the published high-quality studies. Valuable outcomes of the current approach would be directly employed in designing process of similar structures interacting with probable thermomechanical shocks