Sustainable disassembly line balancing model based on triple bottom line

End of life (EOL) phase of a product is receiving more attention due to increase in environmental concerns, and many studies have been conducted for value creation in EOL, focusing on concepts as remanufacturing, reuse and recycling in sustainable production manner. This study especially focuses on one of global problem, e-waste. To minimise the amount of wastes and maximise recovered materials from EOL, disassembly is one of the most important concept, associated with reuse, and balancing disassembly line in an optimal way is essential for organisations. In disassembly line balancing (DLB), not only precedence of tasks, but also risk criteria related to environment and human safety should be considered for sustainability. The aim of this study is to propose a model based on triple bottom line (TBL) dimensions, i.e. human safety, environmental safety and business criteria. To achieve sustainability in DLB, and for risk assessment in sustainable DLB, it had been decided to use a multi-criteria method, i.e. TODIM, acronym in Portuguese of ‘Tomada de Decisão Iterativa Multicritério’. The proposed model included 22 disassembly criteria categorised under TBL dimensions, which are derived from the literature. Implementation of the study was conducted for computer disassembly processes, and as a result of the study approximately 12% an improvement in cycle time was succeeded. In the long run, the integration of sustainability in disassembly operations may contribute to the competitive advantage of the company in terms of differentiation and corporate image by achieving business, environment and human targets simultaneously.     

Masking the Peroxidase-Like Activity of the Molybdenum Disulfide Nanozyme Enables Label-Free Lipase Detection

Two-dimensional MoS₂ nanoparticles (2D-nps) exhibit artificial enzyme properties that can be regulated at bio-nanointerfaces. We discovered that protein lipase is able to tune the peroxidase-like activity of MoS₂ 2D-nps, offering low-nanomolar, label-free detection and identification in samples with unknown identity. The inhibition of the peroxidase-like activity of the MoS₂ 2D-nps was demonstrated to be concentration dependent, and as low as 5 nm lipase was detected with this approach. The results were compared with those obtained with several other proteins that did not display any significant interference with the nanozyme behavior of the MoS₂ 2D-nps. This unique response of lipase was characterized and exploited for the successful identification of lipase in six unknown samples by using qualitative visual inspection and a quantitative statistical analysis method. The developed methodology in this approach is noteworthy for many aspects; MoS₂ 2D-nps are neither labeled with a signaling moiety nor modified with any ligands for signal readout. Only the intrinsic nanozyme activity of the MoS₂ 2D-nps is exploited for this detection approach. No analytical equipment is necessary for the visual detection of lipase. The synthesis of the water-soluble MoS₂ 2D-nps is low costing and can be performed in bulk scale. Exploring the properties of 2D-nps and their interactions with biological materials reveals highly interesting yet instrumental features that offer the development of novel bioanalytical approaches.     

Can the uncertainty in brass casting blending problem be managed? A probability/possibility transformation approach

Problems about the uncertainty in raw material compositions are a critical issue for the blending problems. It is feared that uncertainty in raw material compositions would often cause percent values of the actual blend to go out of specification limits. In this paper, the aleatory and epistemic uncertainties have been handled simultaneously in a blending optimization problem for brass casting. The aleatory and epistemic uncertainties are modeled by using probability and possibility theories respectively. However, the probabilistic and the possibilistic uncertainties are different from the each other. Therefore to solve the mathematical model, including these uncertainties, a transformation of any type of uncertainty to the other is needed. In this study, probabilistic uncertainties are transformed to the possibilistic uncertainties by considering Rong and Lahdelma’s (2008) and the Dubois, Prade, and Sandri (1993) and Dubois, Foulloy, Mauris, and Prade (2004) transformation approaches. This transformation process converts the former model to a possibilistic model. Then the possibilistic models, obtained from each transformation, are solved by using α cuts approach. The solutions of the two possibilistic models have shown that the model, which uses Dubois’s transformation, prepares blends with lower cost than the other model, which uses Rong and Lahdelma’s transformation.     

The hydro-abrasive erosion wear behavior of duplex-treated surfaces of AISI H13 tool steel

The influence of duplex surface treatments consisting of a DC-pulsed plasma nitriding process and subsequent coatings of CrN and TiAlN deposited by physical vapor deposition(PVD)on AISI H13 tool steel was studied in this article.The treated samples were characterized using metallographic techniques,SEM,EDS,and microhardness methods.Hydro-abrasive erosion wear tests were performed in a specifically designed wear tester in which the samples were rotated in a wear tank containing a mixture of distilled water and ceramic abrasive chips with a fixed rotational speed.The wear rates caused by the abrasive particle impacts were assessed based on accumulated weight loss measurements.The worn surfaces were also characterized using optical microscopy,SEM,and EDS.Microhardness measurements indicated a significant increase in the surface hardness of the duplex-treated samples.The surfaces of the samples with the TiAlN coating were approximately 15 times harder than that of the untreated samples and 3 times that of the plasma nitrided samples.Hydro-abrasive erosion wear results showed that the duplex surface treatments,especially the CrN coating,displayed the highest erosion wear resistance.     

Experimental study of a micro-scale sloped solar chimney power plant

Journal of Mechanical Science and Technology - Solar chimney power plants (SCPP) are structures that have the potential to generate a significant amount of electrical energy without harming the...     

A simulation as a service cloud middleware

Many seemingly simple questions that individual users face in their daily lives may actually require substantial number of computing resources to identify the right answers. For example, a user may want to determine the right thermostat settings for different rooms of a house based on a tolerance range such that the energy consumption and costs can be maximally reduced while still offering comfortable temperatures in the house. Such answers can be determined through simulations. However, some simulation models as in this example are stochastic, which require the execution of a large number of simulation tasks and aggregation of results to ascertain if the outcomes lie within specified confidence intervals. Some other simulation models, such as the study of traffic conditions using simulations may need multiple instances to be executed for a number of different parameters. Cloud computing has opened up new avenues for individuals and organizations with limited resources to obtain answers to problems that hitherto required expensive and computationally-intensive resources. This paper presents SIMaaS, which is a cloud-based Simulation-as-a-Service to address these challenges. We demonstrate how lightweight solutions using Linux containers (e.g., Docker) are better suited to support such services instead of heavyweight hypervisor-based solutions, which are shown to incur substantial overhead in provisioning virtual machines on-demand. Empirical results validating our claims are presented in the context of two case studies.     

Convergence of rule-of-thumb sizing and allocating rules of distributed generation in meshed power networks

This paper presents different approaches to find out and address some rules for distributed generation (DG) integrated mesh type networks, which can be used in the management of future power systems. There are so many influencing factors of efficiency in the integration of DG that we need to analyze these influencing factors obviously. Hence, carefully planning plays a key role in tackling these challenges in the future power systems. In contrast to the majority of existing observations, we focus on the case where the underlying states are multiple and single DG allocations with changing conditions. In several previous studies, the best single bus has been investigated under the specified conditions. However, it follows from the results of this study that all issues concerning DG strongly depend on power network structure and DG locations, and it is worth to note that the best location changes with penetration levels. Also, it is observed that the all buses show different characteristics in terms of DG integrations under the different cases, moreover their optimum size and power factor are different. It means that optimum bus in a network changes with the conditions. On the other hand, the problematic buses can be occurred in voltage profile after the DG integration. As a result, an investigation of rule of thumb approach is performed for evaluation of performance enhancement of DG integrated meshed networks. The results are also used to discuss the integration of DG management strategies under various operating conditions.