Integration of a GA and PSO for discussing the impact of 3C product engineering changes on customisation degree

Computer, Communication, Consumer (3C) electronics products have high uncertainty of demand as customers often change their demands. Therefore, manufacturers have to deal with Engineering Change (EC) situations to meet the needs of customers. Based on a literature review, this study has found that a Genetic Algorithm (GA) can yield optimal solutions for ECs, and that Particle Swarm Optimisation (PSO) can more efficiently converge to the optimal solution. Therefore, this study integrated the GA and PSO to determine the optimal manufacturing makespan upon ECs. For 3C products, customer preference is affected by customisation degree. This study developed a deviation utility loss-based customisation degree model that can indicate the gap between the makespan required by customers and optimal makespan from manufacturers upon ECs, as well as the impact of changes on unit price and fixed cost of product of the customisation degree upon EC and parameter change of the customisation degree model. The findings can provide 3C manufacturers with references to select the optimal parameters for difference situations.     

A probabilistic solid-porous model to determine the shear strength of unsaturated soils

A probabilistic solid-porous model has been developed to determine the shear strength of unsaturated soils. The probabilistic model was built by analyzing the probability of a certain pore or group of pores of a network to fill or remain filled with water during a wetting or drying process, respectively. This model is used to determine the equivalent stress which represents the stress supported by the solid skeleton of an unsaturated soil and is related to the strength of the material. The probabilistic model is an alternative to the use of computational models and shows some important advantages. The theoretical results of the model are compared with a series of triaxial tests performed at constant suction and constant volume. These comparisons demonstrate that this model is adequate to establish the strength of unsaturated materials.     

Application of a computer model to evaluate the ability of plastics to act as functional barriers

A simulation model computer program, which accounts for not only the diffusion process inside the polymer but also partitioning of the contaminant between the polymer and the contacting phase, was developed based on a numerical treatment, the finite element method, to quantify migration through multilayer structures. The accuracy of the model in predicting migration was demonstrated successfully by comparing simulated results to experimental data. For this study, three‐layer co‐extruded high density polyethylene (HDPE) film samples, having a symmetrical structure with a contaminated core layer and virgin outer layers as the functional barriers, were fabricated with varying thickness of the outer layers and with a known amount of selected contaminant simulant, 3,5‐di‐t‐butyl‐4‐hydroxytoluene (BHT), in the core layer. Migration of the contaminant simulant from the core layer to the liquid food simulants was determined experimentally as a function of the thickness of the outer layer at different temperatures. The computer program, developed as a total solution package for migration problems, can be applied not only to multilayer structures made with the same type of plastics but also to structures with different plastics, e.g. PP/PE/PP. This work might provide the potential for wider use of recycled plastic, especially polyolefins, which have lower barrier properties, in food packaging, and simplification of the task of convincing the FDA that adequate safety guarantees have been provided. Copyright © 2003 John Wiley & Sons, Ltd.     

A decision model to determine the number of shuttles in a tier-to-tier SBS/RS

Shuttle-based storage and retrieval systems (SBS/RSs), which are designed to increase throughput capacity and flexibility, are a type of automated storage and retrieval system used for lightweight loads. SBS/RSs can increase throughput capacity by using multiple shuttles and elevators as storage and retrieval machines (SRMs). They can also facilitate improvements in flexibility since they are able to adjust the number of SRMs according to transaction demands. Thus, determining the number of shuttles is an important issue in tier-to-tier SBS/RSs. In this paper, a decision model to determine the number of shuttles is proposed. The model is based on the travel time model, and it considers parameters such as the physical configuration, velocity profile and the probability that the shuttle operates a dual command. Finally, the throughput capacity from the travel time model is compared with that from a simulation-based approach in order to verify the effects of the model. In addition, a critical discussion regarding the characteristics of the tier-to-tier system is provided.     

A novel Bayesian approach to reliability modeling: The benefits of uncertainty evaluation in the model selection procedure

This paper proposes a different likelihood formulation within the Bayesian paradigm for parameter estimation of reliability models. Moreover, the assessment of the uncertainties associated with parameters, the goodness of fit, and the model prediction of reliability are included in a systematic framework for better aiding the model selection procedure. Two case studies are appraised to highlight the contributions of the proposed method and demonstrate the differences between the proposed Bayesian formulation and an existing Bayesian formulation.     

Blockchain applied to the construction supply chain: A case study with threat model

The construction industry has long faced the challenge of introducing collaborative systems among multiple stakeholders. This challenge creates a high level of rigidity in terms of processing shared information related to different processes, robust holistic regulations, payment actualizations, and resource utilization across different nodes. The need for a digital platform to cross-connect all stakeholders is necessary. A blockchain-based platform is a prime candidate to improve the industry in general and the construction supply chain (CSC) in particular. In this paper, a literature review is presented to establish the main challenges that CSC faces in terms of its effects on productivity and efficiency. In addition, the effect of applying blockchain platforms on a case study is presented and analyzed from performance and security level. The analysis aims to emphasize that blockchain, as presented in this paper, is a viable solution to the challenges in the CSC regardless of the risks associated with the security and robustness of the flow of information and data protection. Moreover, a threat analysis of applying a blockchain model on the CSC industry is introduced. This model indicates potential attacks and possible countermeasures to prevent the attacks. Future work is needed to expand, quantify, and optimize the threat model and conduct simulations considering proposed countermeasures for the different blockchain attacks outlined in this study.     

A novel Bayesian strategy for the identification of spatially varying material properties and model validation: an application to static elastography

The present paper proposes a novel Bayesian, a computational strategy in the context of model‐based inverse problems in elastostatics. On one hand, we attempt to provide probabilistic estimates of the material properties and their spatial variability that account for the various sources of uncertainty. On the other hand, we attempt to address the question of model fidelity in relation to the experimental reality and particularly in the context of the material constitutive law adopted. This is especially important in biomedical settings when the inferred material properties will be used to make decisions/diagnoses. We propose an expanded parametrization that enables the quantification of model discrepancies in addition to the constitutive parameters. We propose scalable computational strategies for carrying out inference and learning tasks and demonstrate their effectiveness in numerical examples with noiseless and noisy synthetic data. Copyright © 2012 John Wiley & Sons, Ltd.     

A dynamic cluster structure-dependent drag coefficient model applied to the riser in high density circulating fluidized bed

A dynamic cluster structure dependent (DCSD) drag model based on energy dissipation minimization using the two-fluid model (TFM) and the kinetic theory of granular flow (KTGF) is applied to the riser in high density circulating fluidized bed (HDCFB). The characteristics of gas and solid are predicted by means of the DCSD drag model with the convective and local accelerations. The law of granular collision energy dissipation and drag energy dissipation are compared and the influence of granular collision energy dissipation to agglomerate structure is researched. The study shows that granular collision energy dissipation has great influence on heterogeneous structure of riser. Simulated solid volume fraction, axial pressure drop and solid mass flux are compared to experimental measurements, numerical analysis suggests that the temporal-spatial heterogeneous structure characteristics and particle collision affect the flow of the riser in the literature.