A bill of materials-based approach for end-of-life decision making in design for the environment

Re-use, recycling or remanufacturing of products and components are good alternatives for reducing the environmental problems resulting from the huge amounts of waste currently arriving at landfills. A new approach is proposed in this paper for enhancing these alternatives from the earliest stages of product design. Given the product structure (obtained from its bill of materials (BOM)) and the joining and geometrical relationships among the components (obtained from the three-dimensional, computer-aided design representation), a model is proposed that will determine the EOL (EOL) strategy, i.e. the depth of disassembly inside the structure and the final end (re-use, recycle, remanufacture or disposal) for each disassembled part leading to the highest profit. A scatter search (SS) metaheuristic is used to determine the disassembly cost at each level of the BOM. The model presents a number of major improvements with respect to previous research. It addresses the problems of simultaneously determining both the best EOL strategy and the disassembly sequence, as well as allowing removal of components not only over the two or three Cartesian axes and affording the possibility of modifying the encountered strategy in a further step so as to fulfil other business criteria (such as disassembly time, resources availability or maximum waste generation rate).     

Assessing the economic and environmental impact of remanufacturing: a decision support tool for OEM suppliers

The circular economy is often presented as a solution for companies to increase the sustainability of their business. In many situations where suppliers produce subassemblies or modules for OEMs in a B2B context, dependency on their clients limits their options for profitable closed-loop supply chains. In this paper, we develop a simple tool suppliers can use to quickly assess whether remanufacturing is economic and environmentally attractive compared to producing new components. We derive optimal acquisition and reuse quantities that minimise total costs. Based on our analysis with a supplier in the automotive industry, we find that used core prices and remanufacturing yield rates have a large impact while an optimised design for remanufacturing can only marginally improve the situation. The tool is applicable to a wide variety of suppliers and industries that remanufacture their modules or subassemblies, or are exploring the option to engage in remanufacturing operations.     

Fused Deposition Modeling for Unmanned Aerial Vehicles (UAVs): A Review

Additive Manufacturing (AM) is a game changing production technology for aerospace applications. Fused deposition modeling is one of the most widely used AM technologies and recently has gained much attention in the advancement of many products. This paper introduces an extensive review of fused deposition modeling and its application in the development of high performance unmanned aerial vehicles. The process methodology, materials, post processing, and properties of its products are discussed in details. Successful examples of using this technology for making functional, lightweight, and high endurance unmanned aerial vehicles are also highlighted. In addition, major opportunities, limitations, and outlook of fused deposition modeling are also explored. The paper shows that the emerge of fused deposition modeling as a robust technique for unmanned aerial vehicles represents a good opportunity to produce compact, strong, lightweight structures, and functional parts with embedded electronic.

     

A proposed occupational health and safety risk estimation tool for manufacturing systems

There are numerous hazards to be found in almost any workplace. Annually, millions of workers die, are injured or become ill as a result of these occupational hazards. Industrial machines are often involved in these occupational accidents. Because of the demands of regulatory compliance, and the potentially high cost in terms of human suffering and lost production, businesses should place particular emphasis on safety measures. Risk is defined as a combination of the probability of harm and the severity of its consequences. Generally, risk estimation involves examining the hazards associated with a situation or with the use of a machine. A large number of techniques have been proposed for risk estimation, and recent studies have revealed that some of them have serious flaws. The main objective of this paper is to develop a proposed risk assessment tool based on the findings of an earlier study. Our research results constitute a first step towards the integration of occupational health and safety (OHS) concerns into facility planning models which traditionally do not consider OHS. The proposed risk estimation tool is developed based on the characteristics, strengths and weaknesses of 31 existing risk estimation tools, and is then applied to 20 scenarios representing different hazardous situations. To evaluate the performance of the proposed tool, the results were compared with those of other risk estimation tools and confirmed its proposed ability to estimate risk relative to other risk estimation tools.     

Hot wire chemical vapor processing (HWCVP) — A prospective tool for VLSI

Today the Very Large Scale Industry (VLSI) is looking towards process solutions, which will avoid the problems associated with the conventional or presently employed technologies. This demand has become more intense with the VLSI industry extending their horizons towards Micro electro-mechanical systems (MEMS) based devices and Application-Specific Integrated Circuits ASICs). The areas of concern are development of high-k dielectric thin films, highly conducting polysilicon thin films, ultra thin diffusion barriers on low dielectric constant layers with electromigration resistant metal interconnects. Over the last few years, work carried out on the hot wire chemical vapor process (HWCVP) has shown that, this technique has great potential to yield the desired materials at low processing temperatures. This paper discusses the results we have obtained in the above areas and also the extension of application of this technique to areas like MEMS and ASICs.     

Enterprise resource planning (ERP) operations support system for maintaining process integration

A successfully adopted and implemented enterprise resource planning (ERP) system does not automatically guarantee full benefits. It is important that ERP is operated as planned and thus provides the real-time information with a desired level of process integration. Any ERP system pushes a company toward full process integration and solves the fragmentation of information. However, the tight process integration involves operational issues that must be carefully managed. Thus, a conjecture can be made that a centrally coordinated support system is required to assist ERP users and administrators find problems, perform tedious validation and verification, and maintain the process integration of ERP with great consistency. This paper proposes an ERP operations support system (EOSS) that aims to achieve and maintain the process integration of ERP. EOSS monitors the operational status of process integration, prevents anomalies as early as possible and conducts repairs as soon as possible.     

A methodology for design and reconfiguration of reconfigurable bending press machines (RBPMs)

Customer requirements have become very dynamic and unprecedented. A manufacturing paradigm called reconfigurable manufacturing system was initiated to adjust the physical machine entities. The main enabler of a machine structure’s reconfigurability is a modular design approach. The paper explains a function-driven object-oriented methodology for the design and reconfiguration of RBPMs. The complete method aims to optimise initial design of RBPMs, followed by subsequent design of RPBM modules which are stored in a module library so as to enable full-automatic reconfiguration of the RBPMs. The methodology is implemented on a pilot project to design a 145 ton bending capacity RBPM, with a maximum reconfigured length of 5?m and total height of 3?m. In order to deduce the design for the reconfigurable bending press machine, the reconfigurability needs were identified first, followed by the construction of a function tree for the machine. The function tree identifies the primary function for the RBPM, which is to bend sheet metal. The primary function is further decomposed to lower level functions until terminal functions are arrived at. The terminal functions are then used to identify the modules for the machine. The modules implement specific brunches of the machine functions.     

The development of a decision support framework for a quantitative risk assessment in multimodal green logistics: an empirical study

The objective of this research was to develop a decision support framework (DSF) to assess quantitative risk in multimodal green logistics. This risk assessment is the combination of a number of models, the failure mode and effects analysis, the risk contour plot, the quantitative risk assessment, the analytic hierarchy process and the data envelopment analysis which can support a user to perform risk assessment in various decisions. The contribution of this research is that the risk assessment model can generate an optimal green logistics route in accordance with weight from the user. The highlight of this DSF is that the quantitative assessment model can reduce bias on risk assessment of logistics route. An in-depth case study, recommendations, limitations and further research are also provided.     

Directed energy deposition (DED) additive manufacturing: Physical characteristics,defects, challenges and applications

Directed energy deposition (DED) is a branch of additive manufacturing (AM) processes in which a feedstock material in the form of powder or wire is delivered to a substrate on which an energy source such as laser beam, electron beam, or plasma/electric arc is simultaneously focused, thus forming a small melt pool and continuously depositing material, layer by layer. DED has several unique advantages compared to other AM processes, such as site-specific deposition and repair, alloy design, and three-dimensional printing of complex shapes. Herein, recent advances as well as the main aspects governing laser-material interactions during the DED process, melt pool thermal behavior, advanced in situ monitoring, and interaction mechanisms are critically reviewed. The most critical processing variables and their influence on the deposited material properties, along with defect formation mechanisms and characterization techniques, are also identified and discussed. An overview of high-end applications, current challenges associated with DED processing, and a critical outlook of the technology are presented.     

Uncorrelated linear discriminant analysis (ULDA): A powerful tool for exploration of metabolomics data

The theory together with an algorithm for uncorrelated linear discriminant analysis (ULDA) is introduced and applied to explore metabolomics data. ULDA is a supervised method for feature extraction (FE), discriminant analysis (DA) and biomarker screening based on the Fisher criterion function. While principal component analysis (PCA) searches for directions of maximum variance in the data, ULDA seeks linearly combined variables called uncorrelated discriminant vectors (UDVs). The UDVs maximize the separation among different classes in terms of the Fisher criterion. The performance of ULDA is evaluated and compared with PCA, partial least squares discriminant analysis (PLS-DA) and target projection discriminant analysis (TP-DA) for two datasets, one simulated and one real from a metabolomic study. ULDA showed better discriminatory ability than PCA, PLS-DA and TP-DA. The shortcomings of PCA, PLS-DA and TP-DA are attributed to interference from linear correlations in data. PLS-DA and TP-DA performed successfully for the simulated data, but PLS-DA was slightly inferior to ULDA for the real data. ULDA successfully extracted optimal features for discriminant analysis and revealed potential biomarkers. Furthermore, by means of cross-validation, the classification model obtained by ULDA showed better predictive ability than PCA, PLS-DA and TP-DA. In conclusion, ULDA is a powerful tool for revealing discriminatory information in metabolomics data.     

一种用于MRP的分块矩阵方法

提出了一种具有广泛适应性的ＭＲＰ分块矩阵计算方法，讨论了该算法的实现、运行效率和实例应用情况。研究和实践结果表明，ＭＲＰ的分块矩阵算法实现简便，处理效率高，且具有一定通用性，具有较好的应用前景。     

Condition-based fault tree analysis (CBFTA): A new method for improved fault tree analysis (FTA), reliability and safety calculations

Condition-based maintenance methods have changed systems reliability in general and individual systems in particular. Yet, this change does not affect system reliability analysis. System fault tree analysis (FTA) is performed during the design phase. It uses components failure rates derived from available sources as handbooks, etc. Condition-based fault tree analysis (CBFTA) starts with the known FTA. Condition monitoring (CM) methods applied to systems (e.g. vibration analysis, oil analysis, electric current analysis, bearing CM, electric motor CM, and so forth) are used to determine updated failure rate values of sensitive components. The CBFTA method accepts updated failure rates and applies them to the FTA. The CBFTA recalculates periodically the top event (TE) failure rate (λ_TE) thus determining the probability of system failure and the probability of successful system operation—i.e. the system's reliability.FTA is a tool for enhancing system reliability during the design stages. But, it has disadvantages, mainly it does not relate to a specific system undergoing maintenance.CBFTA is tool for updating reliability values of a specific system and for calculating the residual life according to the system's monitored conditions. Using CBFTA, the original FTA is ameliorated to a practical tool for use during the system's field life phase, not just during system design phase.This paper describes the CBFTA method and its advantages are demonstrated by an example.     

Collaborative tool for solving human factors problems in the manufacturing environment: the Theory of Inventive Problem Solving Technique (TRIZ) method

In this study an analysis is made regarding the Theory of Inventive Problem Solving Technique (TRIZ), which emerged in Russia in 1946 and has been commonly used in the USA and Europe in the past few last decades. TRIZ is a method that is used successfully to solve the problems arising during the process of product development. Within this study this method is evaluated from the human factors point of view for the first time. In addition, two applications of the adaptation of TRIZ into human factors problems and works on this goal are presented. The benefits of TRIZ when solving such kind problems are also revealed.     

A New Activity-Based Cost （ABC） Mathematical Model

Along with the product prize competition growing intensely, it is apparently important for reasonably distributing and counting cost. But, in sharing indirect cost, traditional cost accounting unveils the limitations increasingly, especially in authenticity of cost information. And the accounting theory circles and industry circles begin seeking one kind of new accurate cost calculation method, and the activity-based cost ( ABC) method emerges as the times require. In this paper, we will build its mathematical model by the basic principle of ABC, and will improve its mathematical model further. We will establish its comparison mathematical model and make the ABC method go a step further to its practical application.     

A multi-level model on automated vehicle acceptance (MAVA): a review-based study

Abstract

Automated vehicle acceptance (AVA) is a necessary condition for the realisation of higher-level objectives such as improvements in road safety, reductions in traffic congestion and environmental pollution. On the basis of a systematic literature review of 124 empirical studies, the present study proposes MAVA, a multi-level model to predict AVA. It incorporates a process-oriented view on AVA, considering acceptance as the result of a four-stage decision-making process that ranges from the exposure of the individual to automated vehicles (AVs) in Stage 1, the formation of favourable or unfavourable attitudes towards AVs in Stage 2, making the decision to adopt or reject AVs in Stage 3, to the implementation of AVs into practice in Stage 4. MAVA incorporates 28 acceptance factors that represent seven main acceptance classes. The acceptance factors are located at two levels, i.e., micro and meso. Factors at the micro-level constitute individual difference factors (i.e., socio-demographics, personality and travel behaviour). The meso-level captures the exposure of individuals to AVs, instrumental domain-specific, symbolic-affective and moral-normative factors of AVA. The literature review revealed that 6% of the studies investigated the exposure of individuals to AVs (i.e., knowledge and experience). 22% of the studies investigated domain-specific factors (i.e., performance and effort ­expectancy, safety, facilitating conditions, and service and vehicle ­characteristics), 4% symbolic-affective factors (i.e., hedonic motivation and social influence), and 12% moral-normative factors (i.e., perceived benefits and risks). Factors related to a person’s socio-demographic profile, travel behaviour and personality were investigated by 28%, 15% and 14% of the studies, respectively. We recommend that future studies empirically verify MAVA using longitudinal or experimental studies.     

Hollow spherical nanocapsules of poly(pyrrole) as a promising support for Pt/Ru nanoparticles based catalyst

Poly(pyrrole) hollow spherical nanocapsules (HSNCs-PPy) were prepared and used as an efficient support matrix to PtRu nanoparticles. γ-Radiation was utilized to load PtRu nanoparticles into Ppy-HSNC matrix. The advantageous characteristics of HSNCs-Ppy/PtRu catalyst as a support matrix for loading PtRu catalysts are presented.     

A neutron detector for (p,np) coincidence studies

A neutron detector with moderate energy resolution (3 MeV) has been built for neutrons in the energy range 75–175 MeV. The detector was designed for coincidence scattering experiments. The design eliminates the need for long neutron flight paths necessary for comparable energy resolution time-of-flight measurements with a comparable efficiency-solid angle product (0.02 msr). The detector consists of thin plastic scintillators in which the neutron undergoes n–p elastic scattering. The second-scattered protons are tracked by drift chambers and detected in a sodium iodide array. The design motivations and features are presented along with results from detailed in-beam experimental tests.