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INTRODUCTION: The flexibility of life cycle inventory (LCI) background data selection is increasing with the increasing availability of data, but this comes along with the challenge of using the background data with primary life cycle inventory data. To relieve the burden on the practitioner to create the linkages and reduce bias, this study aimed at applying automation to create foreground LCI from primary data and link it to background data to construct product system models (PSM). METHODS: Three experienced LCA software developers were commissioned to independently develop software prototypes to address the problem of how to generate an operable PSM from a complex product specification. The participants were given a confidential product specification in the form of a Bill of Materials (BOM) and were asked to develop and test prototype software under a limited time period that converted the BOM into a foreground model and linked it with one or more a background datasets, along with a list of other functional requirements. The resulting prototypes were compared and tested with additional product specifications. RESULTS: Each developer took a distinct approach to the problem. One approach used semantic similarity relations to identify best-fit background datasets. Another approach focused on producing a flexible description of the model structure that removed redundancy and permitted aggregation. Another approach provided an interactive web application for matching product components to standardized product classification systems to facilitate characterization and linking. DISCUSSION: Four distinct steps were identified in the broader problem of automating PSM construction: creating a foreground model from product data, determining the quantitative properties of foreground model flows, linking flows to background datasets, and expressing the linked model in a format that could be used by existing LCA software. The three prototypes are complementary in that they address different steps and demonstrate alternative approaches. Manual work was still required in each case, especially in the descriptions of the product flows that must be provided by background datasets. CONCLUSION: The study demonstrates the utility of a distributed, comparative software development, as applied to the problem of LCA software. The results demonstrate that the problem of automated PSM construction is tractable. The prototypes created advance the state of the art for LCA software.

The final assembly of an aircraft or a spacecraft is a rigorous task that requires full traceability of the parts installed, their fabrication processes, and the assembly work. This is also the case for each of its sub-assemblies. Safety and security go hand in hand in the production of these flying machines, and even more so for satellites and space-shuttles. The many parts and sub-assemblies that compose the final spacecraft, make full traceability a challenging fit, that is almost unsurmountable. Such traceability is not existent today and must be based on documentation of most assembled parts, assembly tasks, and inspection tasks that compose the full spacecraft. In addition, security measures are needed to prevent hostile hacking and unauthorized approach to the space-craft assembly documentation. This paper describes a framework that harnesses smart-contract and blockchain technology to offer traceable and secure documentation of the assembly process. The concept of a Bill-Of-Assembly (BOA) is introduced which incorporates data from the bill of materials, the bill of operations and processes, and the bill of resources (machines and/or operators). The paper describes the use of the BOA with smart-contract and blockchain technology for getting full traceability, safety, and security for the spacecraft. Finally, we show that this BOA data structure could be the backbone of a digital twin of the spacecraft. Future research could extend the proposed approach to other assembly processes such as automotive assembly lines.

For some years now, digitalization has made its way into all phases of the product life cycle. With the help of the modeling language SysML, Model-Based Systems Engineering (MBSE) represents a modern approach in product development. At the same time, the technologies of Industrie 4.0 and digital twin are opening up a new level of efficiency to producing companies. But entertainment technology is also finding its way into business: Virtual Reality (VR) provides an immersive and cost-effective way to perceive products in the early stages of product development. In order to provide these with quickly available data for display and simulation, it is worthwhile to expand the MBSE approach. This work describes how a product model can be extended by a simulative function structure. On the one hand, this work describes how the Cameo System Modeler can be used to extend a product model with a simulative functional structure. On the other hand, it explains how to extend an existing product model by modeling the information required to efficiently and consistently translate an Engineering Bill of Materials (EBOM) into a Manufacturing Bill of Materials (MBOM).

Over the past two decades, globalized outsourcing in the semiconductor supply chain has lowered manufacturing costs and shortened the time-to-market for original equipment manufacturers (OEMs). However, such outsourcing has rendered the printed circuit boards (PCBs) vulnerable to malicious activities and alterations on a global scale. In this article, we take an in-depth look into one such attack, called the “Big Hack,” that was recently reported by Bloomberg Buisnessweek. The article provides background on the Big Hack from three perspectives: an attacker, a security investigator, and the societal impacts. This study provides details on vulnerabilities in the modern PCB supply chain, the possible attacks, and the existing and emerging countermeasures. The necessity for novel visual inspection techniques for PCB assurance is emphasized throughout the article. Further, a review of various imaging modalities, image analysis algorithms, and open research challenges are provided for automated visual inspection.

Publisher Summary The piping isometric is an important drawing that serves several purposes. It is the primary source for material take-off of each pipe configuration in a facility. Material take-off is the process by which each individual component that makes up a pipe configuration is tabulated for purchase or procurement. This means that all piping components (elbows, flanges, nuts, bolts, washers, gaskets, etc.) must be counted so that purchases of those items can be made. The tabulated results are referred to as the bill of materials. Isometrics also serve as fabrication drawings. Once drawn and properly dimensioned, isometrics are provided to fabricators who build each piping configuration. Fabricators will use the completed isometrics to build shop spools. Shop spools are detailed specifically for pipe welders and fitters with precise cut-lengths and weld symbols. After configurations are fabricated, X-rayed, painted, and shipped to the construction site, isometric drawings serve as an aid to the construction and erection of the facility by providing workers with the locations of tie-ins, connections, and routings.

The study focuses on introducing the design of an efficient automated solar lawn mower. This autonomous vehicle is equipped with sensory unit to avoid obstacles, houses a powerful solar panel along with solar tracking system and carries an electromagnetic trimmer which cuts grass. The model of the mower passed through several inspection simulations to refine and perfect its design. The concern of the end users were taken into consideration and several technical analysis including Kano model assessment, Quality Function Deployment, Function Structure, Bill of Materials, Material Selection and Manufacturing Process Selection were used as the baseline for making any decision regarding the lawn mower. The product features were selected based on the Kano Model of customer need assessment. The Quality Function Deployment converted the customer needs into technical requirements which helped in developing the function structure. Later the function structure aided in designing the product and accelerated the selection of materials and manufacturing processes. The purpose of this project is to assemble the necessary building blocks to develop a less costly, durable, portable, driverless, safer and reliable lawn mowing vehicle. &nbsp

Quality assurance is often a time-consuming and error prone process for organisations. However, it is increasingly important for companies that produce fabricated products for integration into safety critical environments. For example, creating pipe systems for the pharmaceutical industry will include additional risks. As a result, increased regulation is required, which has resulted in further paperwork and validation for companies operating in this sector.A lot of the isometric drawings provided to companies for fabrication remain in paper format (or scanned paper documents). This provides an administrative burden on these companies as the average project could generate up to 5,000 isometric drawings. This research explores techniques that could be utilised to automatically extract Bill of Materials (BOM) information from these isometric drawings.Tesseract has failed to perform OCR accurately on the extracted Region of Interest (ROI) data containing the BOM information, achieving a mean average of 43.8%. This paper explores different pre-processing techniques to increase the accuracy of recognition. Techniques such as binarisation, erosion, noise reduction and contouring were employed to increase this accuracy. In the study, the accuracy increased to a mean average of 81.2%. This has demonstrated that effective use of pre-processing can have an impact on character recognition.

PurposeThe purpose of this paper is to investigate effects on global supply chain reconfigured in the customs duty rate of parts and specific material types brought about by Brexit and the Trans-Pacific Partnership (TPP).Design/methodology/approachThe supply chain network is modeled and formulated using mixed integer programming. Numerical experiments are conducted using bill of materials with information such as the procurement cost of each part, 3D-CAD and an industry census.FindingsThe experiments indicates that if the customs duty rate increases by Brexit, manufacturers would be necessary to restructure supply chain configuration and locate the domestic factory and market. Additionally, when the UK leaves the EU and joins the TPP, there is a case where the total cost decreases in the global supply chain network compared to the baseline without Brexit. Therefore, it is reasonable for the UK to join the TPP.Practical implicationsThe study shows how new trading rules from non-partnership countries can critically disrupt existing global supply chain equilibrium. Asian manufacturers should evaluate a move to more local sourcing, opening new facilities and setting up warehouses to stock finished goods or raw materials in different trading areas to overcome any barriers to the goods movement.Originality/valueThis study enables us to quantitatively evaluate what there are opportunities or cost increasing risks by the selection of supply chain configuration for Asian manufacturers by political and economic factors of each country, such as Brexit and participation in TPP.

Traction batteries are a key factor in the environmental sustainability of electric mobility and, therefore, it is necessary to evaluate their environmental performance to allow a comprehensive sustainability assessment of electric mobility. This article presents an environmental assessment of a lithium-ion traction battery for plug-in hybrid electric vehicles, characterized by a composite cathode material of lithium manganese oxide (LiMn2O4) and lithium nickel manganese cobalt oxide Li(NixCoyMn1-x-y)O2. Composite cathode material is an emerging technology that promises to combine the merits of several active materials into a hybrid electrode to optimize performance and reduce costs. In this study, the environmental assessment of one battery pack (with a nominal capacity of 11.4 kWh able to be used for about 140,000 km of driving) is carried out by using the Life Cycle Assessment methodology consistent with ISO 14040. The system boundaries are the battery production, the operation phase and recycling at the end of life, including the recovery of various material fractions. The composite cathode technology examined besides a good compromise between the higher and the lower performance of NMC and LMO cathodes, can present good environmental performances. The results of the analysis show that the manufacturing phase is relevant to all assessed impact categories (contribution higher than 60%). With regard to electricity losses due to battery efficiency and battery transport, the contribution to the use phase impact of battery efficiency is larger than that of battery transport. Recycling the battery pack contributes less than 11% to all of the assessed impact categories, with the exception of freshwater ecotoxicity (60% of the life cycle impact). The environmental credits related to the recovery of valuable materials (e.g. cobalt and nickel sulphates) and other metal fractions (e.g. aluminium and steel) are particularly relevant to impact categories such as marine eutrophication, human toxicity and abiotic resource depletion. The main innovations of this article are that (1) it presents the first bill of materials of a lithium-ion battery cell for plug-in hybrid electric vehicles with a composite cathode active material; (2) it describes one of the first applications of the life cycle assessment to a lithium-ion battery pack for plug-in hybrid electric vehicles with a composite cathode active material with the aim of identifying the “hot spots” of this technology and providing useful information to battery manufacturers on potentially improving its environmental sustainability; (3) it evaluates the impacts associated with the use phase based on primary data about the battery pack's lifetime, in terms of kilometres driven; and (4) it models the end-of-life phase of the battery components through processes specifically created for or adapted to the case study.

Purpose. This article discusses the process of developing an ergonomic desk for students through an integrated product team approach. Methodology. Using an integrated product team approach, numerou...

This research aims to contribute to quantifying whole building life cycle assessment using various software tools to determine how they can aid the construction industry in reducing carbon emissions, and in particular embodied emissions, through analysis and reporting. The conducted research seeks to examine and compare three whole building life cycle assessment tools; Athena Impact Estimator, Tally and One-Click LCA to relate the input variability to the outputs of the three programs. The three whole building life-cycle assessments were conducted using a case study building with an identical bill of materials and compared to determine the applicability and strengths of one program over another. The research confirmed that the three programs output significantly different results given the variability in scope, allowable program inputs and generated “black-box” back-end calculations, where the outputted whole building life cycle carbon equivalents of One-Click LCA is less than half than of Tally meaning the programs outputs cannot be simply compared side-by-side.

End of Life (EoL) products management through crude recycling methods and direct shredding causes severe threat to environment by different kinds of pollution. The environmental benefits such as reduced CO2 emissions observed through recycling are mitigated by the direct release of toxic gases. De-manufacturing through systematic disassembly operations can reduce environmental damage but it requires more input cost to work within the threshold limit value (TLV). Complete disassembly sequence planning (CDSP) methods are not given importance in de-manufacturing objectives, which produce non-optimal solutions. The objective of present work is to produce an optimal solution to extract valuable materials from the EoL products while separating the toxic elements within TLV. A multi-layered method has been proposed that consists of five different layers, namely data input layer, application layer, modification layer, implementation layer and performance layer. It requires product bill of materials (BOM) and disassembly attributes such as liaison, geometric feasibility and stability as input from the user and generates an optimal solution by suggesting permissible operations to work within TLV. The proposed method has been applied on a case study and workability at producing practically feasible optimal solution has been confirmed. The effectiveness in working has been evaluated by comparing to the existing DSP methods. The proposed method can be used as a tool to achieve maximum profits through systematic disassembly operations within TLV by supplying essential information.

In this paper, we present the need for specialized artificial intelligence (AI) for counterfeit and defect detection of PCB components. Popular computer vision object detection techniques are not sufficient for such dense, low inter-class/high intra-class variation, and limited-data hardware assurance scenarios in which accuracy is paramount. Hence, we explored the limitations of existing object detection methodologies, such as region based convolutional neural networks (RCNNs) and single shot detectors (SSDs), and compared them with our proposed method, the electronic component localization and detection network (ECLAD-Net). The results indicate that, of the compared methods, ECLAD-Net demonstrated the highest performance, with a precision of 87.2% and a recall of 98.9%. Though ECLAD-Net demonstrated decent performance, there is still much progress and collaboration needed from the hardware assurance, computer vision, and deep learning communities for automated, accurate, and scalable PCB assurance.

When the product family (PF) and the supply chain designs (SCD) are aligned and integrated, original equipment manufacturers (OEM) are more likely to improve their operational performance. In this paper, we propose a novel approach, which demonstrates how both the product and the supply chain can simultaneously be designed based on real-time data. At the heart of the proposed model is the utilisation of a cloud-based management system comprising of three steps. In the first step, a generic bill of materials is modelled to design a set of product families using “AND” and “OR” nodes. In the second step, a cloud-based framework is designed to manage real-time costs viz. echelons. In the third step, a mixed integer linear programming model is then applied, which optimizes the SCD based on real-time costs. We use a metaheuristic method based on Genetic Algorithm (GA) to solve the optimization problem. We further illustrate the model using power transformer numerical example. Then the critical parameters of GA are examined to determine the best settings. We believe that the proposed SCD is an intelligent and expert management system, which can facilitate effective decision-making support by taking into account real-time cost data. This is particularly important when there are uncertain and volatile market conditions.

Truss optimization has the goal of achieving savings in costs and material while maintaining structural characteristics. In this research a 10 bar truss was structurally optimized in Rhino 6 using genetic algorithm optimization method. Results from previous research where sizing optimization was limited to using only three different cross-sections were compared to a sizing and shape optimization model which uses only those three cross-sections. Significant savings in mass have been found when using this approach. An analysis was conducted of the necessary bill of materials for these solutions. This research indicates practical effects which optimization can achieve in truss design.

A critical turning point of product commercialization is transferring the product technology and prototype from the R&D facility where the advanced prototype development occurred to the manufacturing facilities (or team) for foundry production. The MEMS product technology must be documented thoroughly to make the transfer process as efficient as possible. In this chapter, we provide an overview of the minimum set of documentation needed for the transfer process and our best practices for effective documentation.

A Bill of Materials (BoM) is the list of all components present on a Printed Circuit Board (PCB). BoMs are useful for multiple forms of failure analysis and hardware assurance. In this paper, we build upon previous work and present an updated framework to automatically extract a BoM from optical images of PCBs in order to keep up to date with technological advancements. This is accomplished by revising the framework to emphasize the role of machine learning and by incorporating domain knowledge of PCB design and hardware Trojans. For accurate machine learning methods, it is critical that the input PCB images are normalized. Hence, we explore the effect of imaging conditions (e.g. camera type, lighting intensity, and lighting color) on component classification, before and after color correction. This is accomplished by collecting PCB images under a variety of imaging conditions and conducting a linear discriminant analysis before and after color checker profile correction, a method commonly used in photography. This paper shows color correction can effectively reduce the intraclass variance of different PCB components, which results in a higher component classification accuracy. This is extremely desirable for machine learning methods, as increased prior knowledge can decrease the number of ground truth images necessary for training. Finally, we detail the future work for data normalization for more accurate automatic BoM extraction. Index Terms – automatic visual inspection; PCB reverse engineering; PCB competitor analysis; hardware assurance; bill of materials

The main research direction for the disposal of spent lithium-ion batteries is focused on the recovery of precious metals. However, few studies exist on the recycling of LiFePO4 electric vehicle (EV) batteries because of their low recycling value. In addition, a detailed life cycle inventory (LCI) of waste plays a significant role in its life cycle assessment (LCA) for an environmental perspective. In this study, an end-of-life (EOL) LiFePO4 EV battery is disposed to achieve the LCI result. The approach comprises manual dismantling of the battery pack/module and crushing and pyrolysis of cells. The authors classify the dismantling results and use different disposal methods, such as recycling or incineration. Regarding the environmental emissions during pyrolysis, the authors record and evaluate the results according to the experimental data, the bill of materials (BOM), the mass conservation, and the chemical reaction equations. In addition, the electricity power demand is related to the electricity mix in China, and the waste gases and solid residue are treated by using neutralization and landfill, respectively. Finally, the authors integrate the LCI data with analysis data and a background database (Ecoinvent). After the integration of the total emission and consumption data, the authors obtained the total detailed LCI resulting from the disposal of the LiFePO4 vehicle battery. This LCI mainly includes the consumption of energy and materials, and emissions to air, water, and soil, which can provide the basis for the future LCA of LiFePO4 (LFP) batteries. Furthermore, the potential of industrial scale process research on the disposal of spent LiFePO4 batteries is discussed.

Supply chain management philosophy has been adopted by enterprises due to the requirement of customer demand satisfaction in reasonable times under market competition. In case of rapid increase in product demands and/or occurrence of supply problems in materials, enterprises choose holding some amount of safety stock of several materials and products. In this study, a multi-period, multi-product supply chain with different suppliers, material storages, production plants, distribution centers and customers is modeled. To determine the optimal production, supply and storage plans at minimum cost, a mixed-integer programming model is proposed. Capacity, bill-of-materials structure of products and placement of safety stocks are taken into account within the proposed model. Solutions of a set of examples are also presented in order to test the model.

A classroom activity involving the construction, calibration, and testing of electronic circuits was introduced to an advanced hydrology class at the postsecondary level. Two circuits were constructed by students: (1) a water detection circuit and (2) a hybrid relative humidity (RH)/air temperature sensor and pyranometer. The circuits motivated concepts of systems science, modelling in hydrology, and model calibration. Students used the circuits to collect data useful for providing inputs to mathematical models of hydrological processes. Each student was given the opportunity to create a custom hydrological model within the context of the class. This is an example of constructivist teaching where students engage in the creation of meaningful knowledge, and the instructor serves as a facilitator to assist students in the achievement of a goal. Analysis of student-provided feedback showed that the circuit activity motivated, engaged, and facilitated learning. Students also found the activity to be a novel and enjoyable experience. The theory of circuit operation and calibration is provided along with a complete bill of materials (BOM) and design files for replication of this activity in other postsecondary classrooms. Student suggestions for improvement of the circuit activity are presented along with additional applications.

Due to the ever-increasing consumption of resources, various materials and raw materials have become increasingly scarce and consequently expensive. At the same time, energy demand has dramatically increased in global mining operations also intensifying economic pressure. Surprisingly, the recapturing of important raw materials at the end of the product life cycle through recycling is still insufficiently implemented in the supply chain. Recycling is not only a sink for unwanted materials it can become an urban mine. This is especially relevant in Europe, where in comparison to other continents primary raw material mining of bulk materials is rather low. In a situation of scarcity, the exact planning of raw material and material flows for the following months (and sometimes years) has become ever more vital to ensure their timely and sufficient availability for production. A missing piece is the necessary transfer of production information (like bill of materials, BOM) to the recycler because information is typically kept inside the production supply chain. Digital technologies such as Digital Twins can help provide this information to the End-of-Life (EoL) stakeholders (recycling industry) as a means to increase the potential of circular economy. This paper establishes urban mining as an important concept of life cycle management in the circular economy. It uses a case study approach to explore the potential of urban mining for resource savings. The authors demonstrate that urban mining represents a high-impact application of sustainable engineering within life cycle management where Digital Twins help increase impact on sustainability.

This paper provides a cost model to develop early estimates for electronics, electrical, and electromechanical (EEE) parts costs during early design phases for instruments and spacecraft. Often, to support a certified proposal, the EEE parts group is required to generate a detailed cost estimate for instruments and spacecraft during preliminary design phases. This requires a premature development of a detailed bill of materials (BOM) far in advance of the final design and fabrication phases; it is therefore no surprise that EEE parts costs grow as a given design is refined and finalized and the required BOM is established. The aerospace cost estimating community lacks sufficient data and understanding of what contributes to EEE parts costs, which is becoming increasingly critical as many advanced instrument and spacecraft designs are relying more heavily on advanced electronics and field-programmable gate array (FPGA) development. This analysis seeks to identify several high-level parameters that can be identified early in the design phase (pre-Phase A through Phase C) to generate a realistic range of EEE parts. The resulting cost model can be used to inform the EEE parts estimating process, and provide program management with the potential cost range for appropriate reserve allocation. Actual costs of APL missions, instruments, and EEE parts are used. Technical leads provide the potential cost drivers as well as the technical data. These cost drivers (such as parts class, radiation, board area, and complexity of design and requirements) are investigated through multiple linear regression analysis. The regression results are used to develop cost estimating relationships (CERs) by determining the best predictors of EEE parts cost. It benefits the NASA and DoD cost communities to obtain a rough estimate of EEE cost during the design phase to more properly budget and provide a reasonable cost risk assessment.

This paper discusses the need and design for a new power electronics educational board. This teaching board features the ability to be used in DC-DC, DC-AC, and AC-DC instructional labs. The board utilizes silicon (Si) and silicon carbide (SiC) technologies, the latter of which being under minimum examination in existing educational labs. This board is intended to be an open-source product that is available for external ordering at production costs. This paper details the design of the board, including schematics, layouts, and bill of materials. An example lab with the board implemented into a buck converter is also demonstrated.

Coronavirus Disease 2019 (COVID-19) threatens to overwhelm our medical infrastructure at the regional level causing spikes in mortality rates because of shortages of critical equipment, like ventilators. Fortunately, with the recent development and widespread deployment of small-scale manufacturing technologies like RepRap-class 3-D printers and open source microcontrollers, mass distributed manufacturing of ventilators has the potential to overcome medical supply shortages. In this study, after providing a background on ventilators, the academic literature is reviewed to find the existing and already openly-published, vetted designs for ventilators systems. These articles are analyzed to determine if the designs are open source both in spirit (license) as well as practical details (e.g. possessing accessible design source files, bill of materials, assembly instructions, wiring diagrams, firmware and software as well as operation and calibration instructions). Next, the existing Internet and gray literature are reviewed for open source ventilator projects and designs. The results of this review found that the tested and peer-reviewed systems lacked complete documentation and the open systems that were documented were either at the very early stages of design (sometimes without even a prototype) and were essentially only basically tested (if at all). With the considerably larger motivation of an ongoing pandemic, it is assumed these projects will garner greater attention and resources to make significant progress to reach a functional and easily-replicated system. There is a large amount of future work needed to move open source ventilators up to the level considered scientific-grade equipment, and even further work needed to reach medical-grade hardware. Future work is needed to achieve the potential of this approach by developing policies, updating regulations, and securing funding mechanisms for the development and testing of open source ventilators for both the current COVID19 pandemic as well as for future pandemics and for everyday use in low-resource settings.

Combining information technology and green manufacturing theory, the concept of energy consumption bill of materials (ECBOM) are first proposed, which is similar to Manufacturing BOM (MBOM), Plan BOM (PBOM) or other extended BOM for different business scenarios. ECBOM will become an effective informatization aid for green manufacturing in product life cycle including green design, green process, green production, green management, green supply chain, green recycling, green maintenance and green technology. Firstly, this paper defines ECBOM and analyzes the evolution process of its data items, then proposes a BOM multi-view transformation method to convert them into ECBOM. In addition, UML conceptual model of ECBOM and its traversal algorithm are designed to efficiently search data for energy consumption evaluation. Finally, a case study of driving belt mechanism in machine tool is taken as to test the method proposed in this paper and indicates that ECBOM could have a positive impaction green manufacturing.

Underwater exploration, in the last years, has evolved toward a wide adoption of increasingly smaller ROVs (Remotely Operated Vehicle). As a consequence, the need to equip these underwater vehicles with robotic arms is currently rising as well. According to this demand, the paper presents three innovative solutions achieved in the UVMS (Underwater Vehicle-Manipulator System) field. Firstly, the paper proposes a modular architecture for a lightweight underwater robotic arm, which can be mounted on small-sized ROVs. The modular concept of the arm enables several different configurations, each one characterized by the related DOFs, deployed according to the type of application to be performed. Secondly, the arm has been equipped with an adaptive gripper that, taking advantage of the additive manufacturing techniques, is able to easily grip differently shaped objects. Lastly, the underwater arm is controlled through a Master–Slave approach, designed for commercial off-the-shelf electronics, that on the one hand, entailed a significant reduction of the bill of materials, but, on the other hand, required a greater effort in the software development. Experimental tests have been carried out to measure and evaluate the gripping and manipulation capability of the robotic arm and the performance of the proposed control system.

This paper focuses on the design of a multi-stage reverse logistics network for product recovery. Different recovery options such as product remanufacturing, component repairing and material recycling are simultaneously considered. Initially, we propose a mixed integer linear programming model – with a profit maximization objective – for the network design problem. The structure of the product, by way of bill of materials (BOM), is also incorporated into the proposed model in order to analyze the flow at component and material levels. Sensitivity analysis is carried out to study the effects of variations in the values of the input parameters such as product return quantity, unit transportation cost per unit distance, and unit processing cost. The analysis shows that the design decisions of different facilities considerably change even for 5–20%% variations in input parameter values. This led to the development of a refined mathematical model which incorporates variations in the different input parameter values over time. The new model provides a unified design for the entire planning horizon and has been validated with the design of a used refrigerator recovery network.

The rapidly evolving trend for increased data rates in today’s and future cellular communication systems poses extreme difficulties for developers of cellular transceivers. A multitude of standards ranging from legacy 2G to the upcoming, yet to be defined, 5G needs to be supported across a broad but fragmented frequency spectrum. Higher data throughput necessitates higher bandwidths, increased number of aggregated carriers, and more complex of modulation schemes. Capable transmitters must exhibit highest in-band performance, e.g. linearity and error vector magnitude. Simultaneously, out-of-band performance, like noise and spurious emissions, is crucial to co-exist with other wireless channels, such as the transceiver’s receivers and other participants. While a “more of everything” is expected, competitive solutions for the wireless market require a constant decrease in silicon area, bill of materials, and especially power consumption. This paper presents the evolution of integrated transmitter architectures facing the above challenges: From conventional analog direct conversion transmitters to fully-digital direct modulation RF transmitters, challenges and benefits are highlighted, presenting modern architectures that benefit from the most advanced technology nodes while supporting upcoming 5G cellular wireless communications.

While it is recognised that there are varying uncertainty characteristics between industry sectors, there is little uncertainty research directly related to engineer-to-order (ETO) systems. A novel method is developed to identify the factors contributing to uncertainty in shipbuilding first-tier suppliers that inhibit the effective and efficient delivery of ETO products. The empirical data set comes from case-specific workshops involving cross-disciplinary staff from engineering, production, purchasing, planning and sales. The protocol included presentations by the researchers and the company, tours of the shopfloor and interactive sessions. The latter used ‘brown-paper’ exercises to map customer penetration-point locations, identify where uncertainties occurred and evaluate their impact-likelihood. The customer penetration-point mapping identified two ETO types; redesign-to-order (RTO) and innovate-to-order (ITO). The major challenges faced by ITO systems are caused through failures in (a) properly understanding customer requirements and translating those to product specification, (b) providing capacity and capability in engineering design teams at both first- and second-tier suppliers, (c) managing interfaces from customer through to second-tier suppliers. Engineering processes in RTO systems have poor customer configuration protocols leading to complex, overengineered products without pre-existing bill of materials. Engineering and production processes at both first- and second-tier RTO suppliers have extended lead-times with poor capacity availability. A change programme is suggested to reduce uncertainty requiring primary consideration of process and control aspects before addressing demand-side and then supply-side changes. The findings are evaluated by independent interviews indicating that the method and tools adopted have validity, and that the findings are commensurate with wider industry expectations.

A indústria da construção civil vem apresentando esforços buscando alcançar os avanços tecnológicos necessários para garantir o constante aumento na qualidade das obras e, consequentemente, melhoria na sustentabilidade de seus produtos. Nesse sentido, a tecnologia Building Information Modeling se destaca como uma forma de permitir que diversas equipes e sistemas se comuniquem e utilizem de uma grande quantidade de informações para avaliar indicadores de desempenho importantes de uma edificação. Por outro lado, a Avaliação de Ciclo de Vida é outra ferramenta importante que pode ser utilizada na seleção de materiais, processos e produtos mais sustentáveis. Portanto, a recente busca pela integração dessas duas tecnologias aparece como uma alternativa viável para garantir que engenheiros, arquitetos e construtores tenham acesso a informações importantes durante qualquer fase no desenvolvimento do projeto e possam, assim, tomar decisões corretas, baseadas em dados providos por sistemas computacionais. Visando essa integração, o presente trabalho apresenta uma abordagem que permite a utilização de bancos de composições de custos para o levantamento de materiais e inventários de ciclo de vida de forma conjunta em ambientes BIM, facilitando a utilização de indicadores ambientais em conjunto com custos. A abordagem é então demonstrada em um estudo de caso de seleção de materiais, demonstrando que, quando comparamos blocos de concreto com blocos cerâmicos para sistemas de alvenarias de vedação, a segunda opção apresenta custos relativamente menores, apesar de ter um maior potencial de influenciar no aquecimento global.

While environmental LCA is relatively well developed, impact assessment methods for the “natural resources” AoP are weak. In particular, resource “criticality” is not addressed in conventional environmental impact assessment methods, though it could be captured within life cycle sustainability assessment. In that regard, the present article extends the previously developed geopolitical supply risk (GPSR) method by demonstrating the connection of criticality to a functional unit while incorporating measures of material substitutability to reflect the “vulnerability” dimension of criticality. The GPSR method developed by Gemechu et al. (J Ind Ecol 20:154–165, 2015a) and subsequently extended by Helbig et al. (J Clean Prod 137:1170–1178, 2016a), and Cimprich et al. (J Clean Prod, 2017) is integrated into an LCIA characterization model. Further, semi-quantitative material substitutability indicator values based on a study by Graedel et al. (PNAS 112:6295–6300, 2015) are incorporated to represent the vulnerability dimension of criticality. The method is demonstrated with an update of a previously published case study of a European-manufactured electric vehicle by Gemechu et al. (Int J Life Cycle Assess 22:31–39, 2015b), along with a new case study of dental X-ray equipment. Due to novel aspects of the GPSR method, the latter case involves constructing an unusually comprehensive bill of materials by tracing unit processes to input commodities with identification codes for collecting commodity trade data. Supply risk “hotspots” are often associated with “minor” commodities such as neodymium in an electric vehicle and cesium iodide in a dental X-ray system. Though difficult to measure, material substitutability can mitigate supply risk. Environmental loads of a dental X-ray system are dominated by production of relatively small specialized functional components like capacitors and printed circuit boards, which are far more environmentally intensive per unit of mass than common structural and mechanical components. Thus, small components comprised of minor materials can “pack a punch” from a supply risk and environmental perspective. The GPSR method presented in the present article brings resource criticality assessment to a product-level while addressing a gap in conventional LCIA methods regarding short-run, socioeconomic availability of natural resources. Further, the case studies illustrate the significance of material substitutability in supply risk assessment. Several complications and limitations of the GPSR method offer directions for future research. Nonetheless, the GPSR method complements environmental LCA to better inform design and management decisions on a product-level.

Increasing performance demands on industrial motion systems often lead to more expensive hardware components and thus a high bill of materials. Given this trend, it is of interest to find solutions that still can provide good performance, but can be used to reduce the overall bill of materials. In this paper, such a solution is proposed by sharing actuation resources between several actuators and using advanced motion control algorithms for the resulting switched system to meet the performance requirements. Obviously, by the sharing of resources, less hardware components are needed, thereby significantly lowering the bill of materials. We demonstrate this solution on an industrial SCARA robot, where it is proposed to use a single amplifier to serve several actuators, rather than a separate amplifier for each actuator. Based on a switched nonlinear model of the robot, switched PID-type controllers are explored that connect to the industrial control practice. The potential of the proposed approach is shown both in simulations and real experiments on an industrial SCARA robot.

New model for manufacturing supply chain design is proposed.The model combines process network and bill of materials with some fuzzy data.Fewer variables and easier to interpret the result than the FLP based models.A real case study is used to demonstrate the applicability of the proposed model. Design of supply chain network significantly affects supply chain performance for long period. Since each industry has a unique set of characteristics which evidently drive the design supply chain network, a number of various models have been formulated to meet the needs of such business contexts. Even though many models have been proposed for manufacturing industry context, most of them are based on the facility location model. It tends to lead the supply chain network design model to be complicated. Therefore, the purpose of this research is to propose an alternative approach to formulate manufacturing network design problem. Features, such as multi-echelon, multi-commodity, products structure, and manufacturing process, are taken into consideration as characteristics of the studied environment. Moreover, uncertainty factors are also integrated to the model by employing possibilistic theory. Eventually in addition to the methodology, a case study in a consumer product firm is used to demonstrate applicability of the proposed method. Two models, deterministic and fuzzy models, have been explored in the study and both of them have demonstrated the validity of the proposed formulation method. Moreover, it is shown that the fuzzy model has outperformed its deterministic counterpart in term of cost effectiveness.

Product development with a high potential for materials recycling is a way to contribute to the conservation of natural resources. Therefore, issues such as product reuse, remanufacturing and reprocessing must be considered during the product design stage. This paper proposes a diagnostic tool to evaluate product recyclability to be applied during the product design phase, acting as a supporting tool for designer decision-making. The potential for recyclability is connected to two factors: materials recycling and disassembly process. For disassembly process, the number, type and accessibility of fasteners were considered. For material recycling process, recycling infrastructure, material compatibility, presence of hazardous materials and existence of contaminants were considered. The proposed indexes are to be used with the product's Bill of Materials (BOM), during the conceptual and embodiment phases of product design. The tool was designed to provide the product's grade of recyclability a graphical diagnosis, aiding the designer in making better design choices. Thus, the designer can diagnose the most critical parts and change the product while still in the design phase, improving the product's recyclability at its end-of-life. A Design for the Environment (DFE) suggestion bank is also provided, to aid the designer in carrying out the improvement decisions. The proposed tool was used in a portable cassette and CD player, simulating its redesign, aiming to improve its end-of-life (EoL) performance. The results demonstrated the ease-of-use of the proposed tool, as well as the importance of having the DFE suggestion bank to give support for improvements.

This article presents a methodology applicable to the formation of collaborative bill-of-materials (C-BOM), coordinating production scheduling and monitoring operational processes. The concept of collaborative product development process is described in detail through an example network, where the participating organisations form a temporary virtual organisation (VO) and contribute throughout the entire product development processes. In this paper, the basic need for exchanging product information among the partners is carried out through IT-based software tools, where the partners are enabled to visualise and monitor the operational processes in a real-time environment. This research study concludes with the overall research outcomes and future research directions.

Global warming requires to reduce greenhouse gas (GHG) emissions in global supply chains. In order to reduce the GHG emissions in the supply chains economically, it needs to estimate the GHG emissions and costs for procuring parts for materials by life cycle assessment (LCA). This study applies the material-based estimation method for the GHG emissions and costs by Yoshizaki et al. (2016) to a cell phone, constructs a bill of materials (BOM) when the materials for parts are produced in Asian countries, and compares the material-based GHG emissions and costs in the cases of cell phone and cleaner.

This research presents a methodology to characterize life cycle impact data (LCIA) of alternative construction materials outside of the European context. This methodology was based on the characterization of data and life cycle assessment (LCA) using geographic information systems (GIS), which has been proposed as an effective alternative for this purpose. The data were characterized at three levels: global, represented by different production efficiency of materials; regional, represented by the type of electricity mix used in the production and the national transport at the country level; and local, represented by external factors, such as seismic and wind risk zones at the city level. A comparative LCA was used as case study to test the methodology. The functional unit for the LCA was defined as an 18 m2 core shelter unit consisting of structural elements only. The bill of materials for five designs were calculated, each using a distinctive construction material: bamboo, brick, concrete hollow block, ferro-cement panels, and soil-stabilised bricks. The contributions’ variability and uncertainty analysis were used to validate the consistency of the results. The effect of the external constraints (earthquakes and wind) were analysed, and the environmental impact over the whole life cycle was assessed. Five house designs were calculated in twenty locations based on three levels of production efficiency and three transport distance ranges for each country. The results of the bamboo, concrete hollow block and ferro-cement houses overlapped and changed depending on the construction materials’ transport distance. Therefore, the level of impact of an average bamboo house can also be achieved by a high-performance block or ferro-cement house. The results showed that in most cases, the buildings with high technical performance can be achieved with low environmental impacts. The use of GIS enables the development of characterized LCIA data for construction materials and buildings with a high degree of consistency. Moreover, the proposed approach was able to accurately represent the range of production practices used outside Europe. Finally, the use of the proposed methodology allows for the assessment of building in the early stages of design when uncertainty is at its highest, thereby identifying the improvement potential of each design and recognising the structural needs in specific locations.

Smart Ship Systems Design (S3D) is a software environment for the definition and assessment of energy distribution systems. A detailed study of high-temperature superconducting (HTS) technologies in a shipboard environment has driven the development of new capabilities and models in the S3D tool. As a result of conducting the HTS study, we introduced into S3D a new capability for quick analysis of thermal systems independently of the electrical systems with which they interact, we improved the method for importing and exporting the bill of materials to facilitate rapid setting of system alignments, we demonstrated a new tool to merge LEAPS databases, and we began testing methods to expand the design space. The study also provided insight for further S3D improvements such as the need for a supervisory controller that optimizes the system operating point to ensure fair analysis of concepts, for a method to prevent cross-connecting of components that are represented in multiple disciplines, and for an API to permit the use of design space exploration methods such as TIES.

Multilevel converters will be one of the most important conversion systems in future power networks. These technologies can facilitate the integration of flexible DER in the grid also getting a significant role in microgrids. Designing high performances converters is not a trivial task due to the numerous different variables involved in the design process. This paper proposes a novel design approach and an easy-to-use executable program, employing a graphical user interface, dedicated to the design of multilevel converters. This software tool aims to obtain multilevel trade-off solutions in terms of efficiency, Mean Time Between Failure and price. The core of this tool consists in a multi-criterion optimization technique, based on the use of an evolutionary genetic algorithm, matched to accurate circuital models (i.e. electro-thermal reliable routine - TER and multilevel converter price routine). The solutions, plotted in two-dimensional and three-dimensional graphics, allow to easily choose the optimal solution for the specific context and visualize the corresponding bill of materials (BOM). The software also permits to consider innovative converter systems employing novel switching devices as the silicon carbide and the gallium nitride types.

This study complies with the reorganization of health care provider processes based on the cost of life cycle of the product. The aim is to determine the costs of treatment administration of extracorporeal dialysis and other treatments in extracorporeal systems. The strategy here was to apply for the first time the “bill of material” (BoM) method to the production and management of the services above. By using standard replacement flows, we build the “bill of materials” to calculate the cost of a CRRT (continuous renal replacement therapy) with anticoagulant. The standard cost of the process is thus obtained. The method here developed can be used for accounting purposes and for economic planning, as a tool for accurate statistical evaluation of medical care.

The paper dwells upon the principles of creating a technological platform for developing an innovative social infrastructure to diagnose and monitor individual and collective power supply systems, building life support, home appliance conditions, Internet of Things devices, and public utilities. The paper proposes novel circuitries and design solutions to optimize and reduce the sizing of the existing energy flux quality monitoring tech by two orders of magnitude. It also proposes: an element-base implementation that considers the complex effects of destabilizing factors; an optimal-topology design of hybrid integrated circuits (HIS) and micro-assemblies; models and algorithms for the statistical estimation of analog-circuit parameter distributions to create an automated subsystem for statistical analysis and optimization of the functional parameters of analog HIS and micro-assembles; an analysis of how process factors affect the reliability of internal connections when assembling components on substrates and connecting the substrate contact pads to the HIS and micro-assembly outputs; as well as a bill of materials and technologies. The conclusion formulates the opportunities to improve the design technology and to design energy-efficient buildings, as well as to provide novel information services (such as power-infrastructure monitoring, etc.) to industries and people alike. Some of the results have been obtained within the research funded by the Russian Ministry of Education and Science under the Project Agreement No. 14.579.21.0158 UID RFMEFI57918X0158.

This Research Note describes the rationale for and design of a XyloScope, a digital imaging system for viewing and recording macroscopic images of wood for a XyloTron machine-vision wood identification system, and provides a bill of materials and the associated technical drawings of its components.

International audience; The need of building process industrialization has seed up the use of new Information Technologies to enhance the productivity and quality of building projects. In particular, the use of the Building Information Modeling (BIM) assets and real time follow-up based on the Cyber Physical System paradigm could be a source of valuable data to support planning and monitoring activities throughout the building life cycle. In the context of process industrialization one challenging issue is the transformation of design data into manufacturing data. The main contribution of this paper is the automatic transformation from engineering bills of material (e-BOM) to manufacturing (m-BOM) ones based on routing sheets and resources’ availability status. Illustrated by an actual prefabricated building case study, a methodological approach to dynamically adapt the e-BOM to m-BOM supported by a generic BOM and its implementation architecture are proposed.

Food and culinary business are growing, especially the variety of consumer demand. Business owners need to continue to develop various food menus to suit consumer needs. Various types of raw materials and food additives are used to produce foods with the best flavour. On the other hand, culinary business owners are required to be able to be adaptive to meet the needs of consumers efficiently and meet the requirements of food safety and halal. The material analysis problem is the complexity of the food menu, and it requires a lot of effort and time to analyse its constituent materials. Therefore, manual checking is not efficient, especially if it had to track the halal and legal information on raw material and food additives. One way to improve the efficiency of raw material uses and identify halal food is to use a bill of material analysis. Through this analysis, business owners can specify raw materials and food additives while recognising the halal nature of the ingredients used. The use of the bill of materials is expected to facilitate menu breakdown and to track the halal of raw materials and additional ingredients. This study aims to analyse food menus in culinary businesses and build a framework of the bill of material standards that can later be used and applied to culinary businesses. This study uses a system analysis and design approach where there is a requirement identification analysis stage as the basis for a framework for developing a bill of materials information system.

Integrating new products into an existing value chain network is a crucial step in a company's strategy to remain competitive. Businesses are evolving in an economy deeply affected by the global development through unstable markets, changes in trade agreements, increased preoccupations with land use and pollution, and technological advancements. Intrinsically, a company creates a product portfolio to target specific market needs, balance resources and capacities, lower market risks, and ensure stable revenue input. Nevertheless, changing markets increasingly complicate the set of parameters that a company must consider when securing an efficient product portfolio. This research aims to help organizations assess prospective products and optimize product integration by detecting synergies of an existing production/distribution network. To this end, we developed an analytics tool in the form of a mixed-integer linear programming model to evaluate a regional production/distribution network's strategical-level decisions. The model allows mathematical representation of a given network composed of divergent manufacturing processes, bill of materials, distribution nodes, and business-to-business circular economy. The model is applied to a realistic case study in Quebec's Mauricie region, where the introduction of eight bioproducts is evaluated for the forest value chain. The processes considered are: pressurized hot water extraction, fast pyrolysis, organosolv fractionation, and kraft lignin recovery. Our results show that biorefineries have potential economic, social and environmental impacts on the existing forest industry but are tightly linked to the governmental subsidies underlying the forest industry's incapacity to self-sufficiently sustain economic long-term viability in its development towards market maturity.

Supplier selection is a common problem for manufacturing industries because there are so many supplier options. The decision support system is one solution that can help industries in which one is the best supplier with specific criteria. In the case of manufacturing industries, to give decisions supports system input data, we need to identify the bill of materials. Furthermore, group technology also can be used to optimize the bill of materials. In this paper, we present the database design process from the bill of materials combined with group technology in tractor manufacturing industries. Product structure diagram, bill of materials table, database design diagram are created as results. From this result, we can develop a decision support system with some computing algorithmsfor the next study.

This paper presents a new practical game which helps undergraduate students to understand how the concept of supply chain management (SCM) works. The game uses a simple supply chain structure incorporating three entities of the supply chain: supplier, plant, and customer. The game employs a set of toy building blocks such as LEGO® blocks and has the rules of the game, responsibility of each player, product descriptions and bill of materials. This competitive game is used supply chain cost as the measuring to determine the winner team of the game and the Bloom's taxonomy as guidelines to develop the assessment testing based on the learning objectives of courses. This proposed board game has been tested by many undergraduate students who are taking SCM and Logistics Management courses. The results show that the students who played the game reached the higher scores of assessment testing than students who didn't play the game. Furthermore, most students have also positive view about this game.

Though life cycle assessment can provide the analytic basis of environmental impact of products for engineering designers, it requires not only a significant amount of time but also a detailed bill of materials of the products to determine the optimal product designs. To overcome the barrier between life cycle assessment and design, in this paper, the optimal product design for life cycle assessment is studied. Instead of comparing a few design alternatives due to the barrier, design variables are allowed to vary as an optimization problem to minimize environmental impact. As a numerical example, the design of universal electric motors was demonstrated. Under the five different design cases, the optimal designs could be achieved to minimize the total environmental impact of universal motors.

The objective of this study is to monitor manufacturing energy consumption (MEC) in a discrete manufacturing enterprise, where energy is consumed everywhere and anytime with creating ubiquitous MEC data. The ubiquitous manufacturing (UbiM) technology, including radio frequency identification (RFID) technique, is employed to automate real-time data acquisition and processing for an order fulfilment. An MEC model for the order fulfilment is constructed according to the bill of materials (BOM). In this model, the computation is triggered by an RFID read event (RRE) enabling a digital energy metre to acquire energy consumption value of a workstation for processing a certain material, and then the acquired value is assigned to an energy consumption event (ECE). To reflect the effect of an ECE on energy consumption of a production task, a station-material energy consumption matrix (smECM) is constructed to store the relevant event data, which plays a key role in alleviating MEC monitoring restrictions caused by big energy data. By operating the matrix, the MEC monitoring information can be effectively extracted. To assist manufacturing enterprises to better employ it, the proposed method was demonstrated by monitoring MEC of an order in an auto-part manufacturer.

The open-source release of self-replicating rapid prototypers (RepRaps) has created a rich opportunity for low-cost distributed digital fabrication of complex 3-D objects such as scientific equipment. For example, 3-D printable reactionware devices offer the opportunity to combine open hardware microfluidic handling with lab-on-a-chip reactionware to radically reduce costs and increase the number and complexity of microfluidic applications. To further drive down the cost while improving the performance of lab-on-a-chip paper-based microfluidic prototyping, this study reports on the development of a RepRap upgrade capable of converting a Prusa Mendel RepRap into a wax 3-D printer for paper-based microfluidic applications. An open-source hardware approach is used to demonstrate a 3-D printable upgrade for the 3-D printer, which combines a heated syringe pump with the RepRap/Arduino 3-D control. The bill of materials, designs, basic assembly, and use instructions are provided, along with a completely free and open-source software tool chain. The open-source hardware device described here accelerates the potential of the nascent field of electrochemical detection combined with paper-based microfluidics by dropping the marginal cost of prototyping to nearly zero while accelerating the turnover between paper-based microfluidic designs.