Life cycle modeling for adaptive and variant design part 2: case study

Life cycle modeling for design (LCMD) facilitates the incorporation of life cycle modeling into product design by including consideration of uncertainty in a products final specifications. The methodology combines Life Cycle Assessment with probabilistic design methods in a way that reduces information needs. Part 1 of this article presents the basic LCMD methodology. Here, in Part 2, LCMD is used to evaluate material substitution opportunities to reduce resource consumption, reduce life cycle air emissions, and increase the recyclable mass for a Ford C-class sedan. In addition to further illustrating LCMD, the case study identifies vehicle design scenarios that offer modest improvements in environmental performance and related cost tradeoffs.

Novel Approach to Improve Electronics Reliability in the Next Generation of US Army Small Unmanned Ground Vehicles Under Complex Vibration Conditions

The functionality of next generation the US Army’s platforms, such as the Small Unmanned Ground Vehicles and Small Unmanned Arial Vehicles, is strongly dependent on the reliability of electronics-rich devices. Thus, the performance and accuracy of these systems will be dependent on the life-cycle of electronics. These electronic systems and the critical components in them experience extremely harsh environments such as shock and vibration. Therefore, it is imperative to identify the failure mechanisms of these components through experimental and virtual failure assessment. One of the key challenges in re-creating life-cycle vibration conditions during design and qualification testing in the lab is the re-creation of simultaneous multiaxial excitation that the product experiences in the field. Instead, the common practice is to use sequential single-axis excitation in different axes or uncontrolled multiaxial vibration on repetitive shock shakers. Consequently, the dominant failure modes in the field are sometimes very difficult to duplicate in a laboratory test. This paper presents the joint effort by the US Army Materiel Systems Analysis Activity (AMSAA) and the Center of Advanced Life Cycle Engineering (CALCE) at the University of Maryland to develop test methods and analytical models that better capture unforeseen design weaknesses prior to the qualification phase, by better replication of the life-cycle vibration conditions. One approach was to utilize a novel multi-degrees-of-freedom (M-DoF) electrodynamic shaker to ruggedize designs for fatigue damage due to multi-directional random vibration. The merits of vibration testing methods with six-DoF shaker and cost saving associated with such an approach will be addressed in this paper. There is a potential for M-DoF to detect critical design vulnerabilities earlier in the development cycle than has been traditionally possible with existing shaker technologies; and therefore to produce more cost effective, reliable and safe systems for the warfighters.     

Eco-redesign of a personal electronic product subject to the energy-using product directive

It cannot be denied that environmental consciousness is becoming important. Ironically, legislation is probably the most satisfactory driver for pushing manufacturers to take environmental concerns into design considerations. In fact, the European Union introduced a new law (directive 2005/32/EC) for regulating the environmental consequences of all energy-using products (EuPs) in August 2007, the scope of which covers all products that rely on energy sources in any form for operation. Design alternatives are required in the product development stage so that environmental concerns can be considered as a decision parameter. In complying with the directive, life-cycle assessment (LCA) is a useful tool to draw conclusions and to compare the performance of alternatives. In this connection, a case study is carried out to assess the environmental impact of a personal electronic product through LCA, subject to the scope of the stated directive. The objectives of this paper are threefold: (i) to report the case in relation to the directive; (ii) to summarise the results of the LCA accordingly; and (iii) to suggest a new conceptual design and to compare the LCA of this new design with the original design.     

Cost optimal design of R/C buildings

A systematic approach is proposed for evaluating the cost-effectiveness of existing or proposed design criteria from the standpoint of life-cycle cost consideration. A series of alternative designs of a model structure representing a class of R/C buildings would be developed following an existing code procedure, except that the code requirements or parameters will be varied for the alternative designs so that a suite of different structures will be obtained each with a different level of safety or reliability. For each of the designed structures, the probability of exceeding the various damage levels under a given earthquake intensity may be calculated. Aggregating and integrating all the cost components with the damage probability density functions for each of the designed structures, as well as with the probabilities of all possible earthquake intensities over a given life will yield the expected life-cycle costs for the respective structures as a function of structural reliability. From these results, the design with the minimum expected life-cycle cost may then be identified; its underlying safety or reliability can also be determined. The approach is illustrated for a class of reinforced concrete buildings under earthquake loading.     

Evaluation of multitransducer arrays for the determination of organic vapor mixtures

A study of vapor recognition and quantification by polymer-coated multitransducer (MT) arrays is described. The primary data set consists of experimentally derived sensitivities for 11 organic vapors obtained from 15 microsensors comprising five cantilever, capacitor, and calorimeter devices coated with five different sorptive-polymer films. These are used in Monte Carlo simulations coupled with principal component regression models to assess expected performance. Recognition rates for individual vapors and for vapor mixtures of up to four components are estimated for single-transducer (ST) arrays of up to five sensors and MT arrays of up to 15 sensors. Recognition rates are not significantly improved by including more than five sensors in an MT array for any specific analysis, regardless of difficulty. Optimal MT arrays consistently outperform optimal ST arrays of similar size, and with judiciously selected 5-sensor MT arrays, one-third of all possible ternary vapor mixtures are reliably discriminated from their individual components and binary component mixtures, whereas none are reliably determined with any of the ST arrays. Quaternary mixtures could not be analyzed effectively with any of the arrays. A "universal" MT array consisting of eight sensors is defined, which provides the best possible performance for all analytical scenarios. Accurate quantification is predicted for correctly identified vapors.     

Life-cycle inventory analysis of concrete production: A critical review

Concrete is one of the most widely used building materials with a global consumption rate approaching 25 gigatonnes per year. Consequentially, its environmental burden is significant in terms of resource use and environmental emissions. There is a diverse audience of decision makers and manufacturers who are interested in understanding and lowering the environmental impact of concrete and other buildings materials, which requires a life-cycle assessment (LCA) approach. A critical first step in any LCA is the compilation of a credible life-cycle inventory (LCI), upon which subsequent life-cycle impact assessment (LCIA) can be based. This article reviews the strengths and weaknesses of concrete LCIs to date, and offers a research roadmap to improve the quality of future cement and concrete LCIs and meet the needs of major LCA users.     

A hierarchical approach to warehouse design

The design of large complex systems, such as warehouses, requires multiple experts and analyses as well as methods to organise and integrate their knowledge. While there are many models for optimising individual aspects of warehouses, there is not, today, a comprehensive design methodology that incorporates and supports all of the design decisions and provides a method to effectively integrate the solutions to these subproblems into a complete warehouse system specification. In this research, we propose a hierarchical design decision support methodology based on decomposing the design problem into a set of subproblems and using a formal model of the system to integrate the solutions to these subproblems. The methodology enables a thorough search of the design space and the identification of many candidate designs for consideration by the design decision maker. The hierarchical design methodology is demonstrated with an example of designing a forward pick area.     

Simultaneous topology and build orientation optimization for minimization of additive manufacturing cost and time

The ever-present demand for increased performance in mechanical systems, and reduced cost and manufacturing time, has led to the adoption of computational design tools and innovative manufacturing methods. One such tool is topology optimization (TO), which often produces designs that are impracticable to manufacture. However, recent developments in additive manufacturing (AM) have made production of such complex designs feasible. Therefore, integration of these technologies has the potential to innovate the design and manufacture of mechanical components. This work presents a novel mathematical methodology for multiobjective minimization of structural compliance and AM cost and time, in simultaneous build orientation and density-based TO. Component surface area and support volume were implemented in this method as the physical factors influencing AM cost and time. A new methodology was produced to approximate support volume throughout TO with variable build orientation, enabling direct minimization of support volume in the proposed optimization. The methodology allows derivation of sensitivity expressions, thereby permitting the use of efficient gradient-based optimization solvers. Three numerical examples demonstrated that the proposed methodology can efficiently produce optimum build orientations and topologies, which significantly reduce structural compliance and AM cost and time.     

A formal method for subjective design evaluation with multiple attributes

This paper contributes toward a more formal theory and methodology for design by mathematically modeling the functional relationships between design decisions and the ultimate overall worth of a design. The conventional approach to design evaluation is limited in two respects. First, the direct measurement of attribute performance levels does not reflect the subsequentworth to the designer. Second, ad hoc methods for determining the relative importance or priority of attributes do not accurately quantify beneficial attribute tradeoffs. This information is critical to the iterative redesign process. A formal Methodology for the Evaluation of Design Alternatives (MEDA) is presented which resolves these problems and can be used to evaluate design alternatives in the iterative design/redesign process. Multiattribute utility analysis is employed to compare the overall utility or value of alternative designs as a function of the levels of several performance characteristics of a manufactured system. The evaluation function reflects the designer's preferences for sets of multiple attributes. Sensitivity analysis provides a quantitative basis for modifying a design to increase its utility to the decision-maker. Improvements in one or more areas of performance and tradeoffs between attributes which would increase desirability of a design most are identified. A case study of materials selection and design in the automotive industry is presented which illustrates the steps followed in application of the method.     

Sustainable manufacturing: a case study of the forklift painting process

Life cycle assessment (LCA) and design for environment (DFE) methods were applied to assess opportunities for reducing the environmental impacts of forklift manufacturing unit processes and to redesign those unit processes to increase overall sustainability. The unit processes of forklift manufacture generating the most environmental emissions were identified by applying LCA methodology. The results show that eco-toxicity and human toxicity were the most significant impacts of the forklift manufacturing process overall. Also, within the manufacturing unit processes, cutting, welding and painting had the highest impact values. In order to minimise environmental impacts, a new paint was created with increased solid content over the existing solvent paint used in the painting process. In addition, by applying DFE methodology and the high solid paint, overcoat and drying steps were eliminated from the forklift painting process. As a result, the environmental index of a follow-up LCA showed that environmental impacts could be reduced by 20%, while volatile organic compound (VOC) and paint usage could be decreased by 30% and 20%, respectively.     

A life cycle methodology for mapping the flows of pollutants in the urban environment

This paper presents an integrated life cycle methodology for mapping the flows of pollutants in the urban environment, following the pollutants from their sources through the environment to receptors. The sources of pollution that can be considered by this methodology include products, processes and human activities. Life cycle assessment (LCA), substance flow analysis (SFA), fate and transport modelling (F&TM) and geographical information systems (GIS) have been used as tools for these purposes. A mathematical framework has been developed to enable linking and integration of LCA and SFA. The main feature of the framework is a distinction between the foreground and background systems, where the foreground system includes pollution sources of primary interest in the urban environment and the background comprises all other supporting activities occurring elsewhere in the life cycle. Applying the foreground–background approach, SFA is used to track specific pollutants in the urban environment (foreground) from different sources. LCA is applied to quantify emissions of a number of different pollutants and their impacts in both the urban (foreground) and in the wider environment (background). Therefore, two “pollution vectors" are generated: one each by LCA and SFA. The former comprises all environmental burdens or impacts generated by a source of interest on a life cycle basis and the latter is defined by the flows of a particular burden (substance or pollutant) generated by different sources in the foreground. The vectors are related to the “unit of analysis" which represents a modified functional unit used in LCA and defines the level of activity of the pollution source of interest. A further methodological development has also included integration of LCA and SFA with F&TM and GIS. A four-step methodology is proposed to enable spatial mapping of pollution from sources through the environment to receptors. The approach involves the use of GIS to map sources of pollution, application of the LCA–SFA approach to define sources of interest and quantify environmental burdens and impacts on a life-cycle basis. This is followed by F&TM to track pollution through the environment and by the quantification of site-specific impacts on human health and the environment. The application of the integrated methodology and the mathematical framework is illustrated by a hypothetical example involving four pollution sources in a city: incineration of MSW, manufacture of PVC, car travel and truck freight.     

Design optimization of an opposed piston brake caliper

Successful brake caliper designs must be light and stiff, preventing excessive deformation and extended brake pedal travel. These conflicting requirements are difficult to optimize owing to complex caliper geometry, loading and interaction of individual brake components (pads, disc and caliper). The article studies a fixed, four-pot (piston) caliper, and describes in detail the computer-based topology optimization methodology applied to obtain two optimized designs. At first sight, relatively different designs (named ‘Z’ and ‘W’) were obtained by minor changes to the designable volume and boundary conditions. However, on closer inspection, the same main bridge design features could be recognized. Both designs offered considerable reduction of caliper mass, by 19% and 28%, respectively. Further finite element analyses conducted on one of the optimized designs (Z caliper) showed which individual bridge features and their combinations are the most important in maintaining caliper stiffness.     

Meso-scale life-cycle impact assessment of novel technology policies: the case of renewable energy

Assessing the environmental risk of novel technological systems and of the European Union (EU) policies supporting them and regulating their implementation requires good understanding of (i) the pressure on the environment posed by the large-scale use of new technology, and (ii) the vulnerability of the receptor of this pressure. Generic life-cycle assessments (LCAs) provide exhaustive accounting of environmental pressure, yet they do not take into account the vulnerability of the receiving ecosystem. Generic studies of technology externalities fail to produce conclusions on the impacts in a certain area of the systems envisaged due to lack of site-specific information. The combined use of generic (LCA) and spatially referenced data offers new opportunities for comprehensively analysing the environmental impact of novel technologies. A novel information fusion methodology is suggested. Example applications are presented herein focusing on the evaluation of renewable energy technologies as an example of the implementation of meso-scale LCA for integrated environmental risk assessment of EU technology policies.     

Fuzzy expected value modelling approach for determining target values of engineering characteristics in QFD

Quality function deployment (QFD) is a planning and problem-solving tool that is renowned for translating customer requirements into the technical attributes of a product. To deal with the imprecise elements in the development process, fuzzy set theory is incorporated into QFD methodology. A novel fuzzy expected value operator approach is proposed in this paper to model the QFD process in a fuzzy environment, and two fuzzy expected value models are established to determine the target values of engineering characteristics in handling different practical design scenarios. Analogous to stochastic programming, the underlying philosophy in the proposed approach is based on selecting the decision with maximum expected returns. Furthermore, the proposed approach considers not only the inherent fuzziness in the relationships between customer requirements and engineering characteristics, but also the correlation among engineering characteristics. These two kinds of fuzzy relationships are aggregated to give the fuzzy importance of individual engineering characteristics. Finally, an example of a quality improvement problem of a motor car design is given to demonstrate the application and performance of the proposed modelling approach.     

Maximization of System Reliability with a Choice of Redundancy Strategies

Optimal solutions to the redundancy allocation problem are determined when either active or cold-standby redundancy can be selectively chosen for individual subsystems. This problem involves the selection of components and redundancy levels to maximize system reliability. Previously, solutions to the problem could only be found if analysts were restricted to a predetermined redundancy strategy for the complete system. Generally, it had been assumed that active redundancy was to be used. However, in practice both active and cold-standby redundancy may be used within a particular system design and the choice of redundancy strategy becomes an additional decision variable. Available optimization algorithms are inadequate for these design problems and better alternatives are required. The methodology presented here is specifically developed to accommodate the case where there is a choice of redundancy strategy. The problem is formulated with imperfect sensing and switching of cold-standby redundant components and k -Erlang distributed time-to-failure. Optimal solutions to the problem are found by an equivalent problem formulation and integer programming. The methodology is demonstrated on a well-known test problem with interesting results. The optimal system design is distinctly different from the corresponding design obtained with only active redundancy. The availability of this tool can result in more reliable and cost-effective engineering designs.     

Complex assembly variant design in agile manufacturing. Part I: System architecture and assembly modeling methodology

In the distributed and horizontally integrated manufacturing environment found in agile manufacturing, there is a great demand for new product development methods that are capable of generating new customized assembly designs based on mature component designs that might be dispersed at geographically distributed partner sites. To cater for this demand, this paper addresses the methodology for complex assembly variant design in agile manufacturing. It consists in fundamental research in two parts: (i) assembly modeling; and (ii) assembly variant design methodology. This paper, the first of a two-part series, presents the assembly variant design system architecture and the assembly modeling methodology. First, a complementary assembly modeling concept is proposed with two kinds of assembly models, the hierarchical assembly model and the relational assembly model. The first explicitly captures the hierarchical and functional relationships between constituent components whereas the second explicitly captures the mating relationships at the form-feature-level. These models are complementary in the sense that each of them models only a specific aspect of assembly-related information but together they include the required assembly-related information. They are further specialized to accommodate the features of assembly variant design. As a result, two kinds of assembly models, the assembly variants model and the assembly mating graph are generated. These assembly models serve as the basis for assembly variant design which is discussed in the companion paper.     

Emergy-based life cycle assessment (Em-LCA) for sustainability appraisal of infrastructure systems: a case study on paved roads

Civil infrastructure systems are critical assets that are subjected to damage, service-life deterioration, and increasing maintenance and rehabilitation cost. Effective infrastructure management and principles of sustainable development can help to find an optimal compromise between economic growth and environmental protection for all stakeholders. Colloquially, sustainability refers to meeting triple-bottom-line (TBL) performance objectives including environmental protection, economic prosperity, and social acceptability and equity as a result of short- and long-term policy decisions. In this paper, a comprehensive framework based on the integration of emergy synthesis and life cycle assessment (LCA) has been investigated for a public infrastructure system. The main purpose of the applied method, emergy-based LCA (Em-LCA), is to facilitate an informed decision making process for different asset management scenarios, by identifying and quantifying the attributes of TBL impacts over the life cycle of a civil infrastructure system. As a case study, Em-LCA framework has been applied to evaluate the sustainability of two different scenarios for a road construction project in interior British Columbia, Canada. The results indicate that Em-LCA offers a good understanding to address sustainability issues in infrastructure systems and provides quantitative and transparent results to facilitate informed decision making for asset management.     

Data quality and uncertainty assessment methodology for pavement LCA

In performing pavement life cycle assessment (LCA), users are facing various reports of energy intensity coefficient (EIC) of pavement materials which differ considerably among data sources and therefore alter the LCA results significantly. Instead of selecting a certain EIC without or of little explanation for the current pavement LCA practices, this study proposed a methodology to build probability density function (PDF) for EIC based on available data-set and their qualities. Each data was first evaluated about the data quality indicator (DQI) through data quality pedigree matrix and converted to PDF in modified Beta distribution form. Three weighting methods, the DQI one, coefficient of variation (COV) one and analytical hierarchy process (AHP) one, were developed to assign weightings for different data. Monte Carlo simulation was run with the weighted PDF of each data as input to obtain the ultimate PDF for EIC. A case study to estimate the bitumen’s EIC with eight data samples were performed using the proposed methodology. It is found (1): the estimates by the proposed methodology is of higher reliability (lower COV) compared to any single data due to utilisation of information of the overall data samples; (2) the AHP weighting method is most favoured despite the results of the three weighting methods are close; (3) the central estimates of bitumen’s EIC are between5.4~5.8 MJ/kg. The proposed methodology is helpful in aiding calculating EICs for pavement materials and capturing uncertainties in LCA results in a statistical sense.