Bill Of Materials Research Articles

Development of Multi-Disciplinary Green-BOM to Maintain Sustainability in Reconfigurable Manufacturing Systems

The reconfigurable manufacturing system (RMS) appears to be eco-friendly while coping with rapidly changing market demands. However, there remains a lack of discussion or research regarding sustainability or environment-friendly functions within RMS. In this study, the reconfiguration planning problem is introduced to represent the core issues within the RMS. Reconfiguration occurs depending on new demands or conditions in the company by reconfiguring machines, such as removing, adding, or changing parts, giving considerable consideration to arrangement of machines, known as configurations in RMS. Therefore, reconfiguration process is always strongly connected to cost, energy consumption, and, more importantly, data management. The complexity of reconfiguration, product variation, and development processes requires tools that are capable of managing multi-disciplinary bill-of-material(BOM) or product data and providing a better collaboration support for data/information tracking while maintaining sustainability. This paper proposes a multi-disciplinary green bill-of-material (MDG-BOM)—an improved Green-BOM concept—with an additional multi-disciplinary feature to minimize emissions and hazardous materials during product development, as well as manage product information across multiple disciplines during the reconfiguration process. A smart spreadsheet for managing MDG-BOM was developed to allow multiple departments to integrate multiple sources of CAD design data and monitor/track changes throughout each step of the process.

Impact of a tunnel on the TL of a vehicle floor in bare and trimmed conditions and investigation on the most suitable simplified geometry able to better represent such impact

NVH engineers are faced with the challenge of designing trim parts for vehicle interior and exterior, like inner dash insulators, carpets, underbody shields or engine encapsulations, which can be made with very different Bills of Materials (BOMs) including among others foams, felts or heavier layers. The measurables commonly used to rank various solutions are Transmission Loss (TL) and absorption. Depending on the numerical analysis method, different approaches may be considered for the evaluation of the TL of an automotive component. In particular, in Statistical Energy Analysis (SEA), automotive components are modeled as an assembly of panels having a simple shape, e.g. flat panels and/or panels with single or double curvature. Furthermore, in SEA the trim is normally modeled by means of the Transfer Matrix Method (TMM), which is essentially a 2-dimensional methodology. This paper intends to analyze in some depth the level of approximation that these practices bring with themselves, specifically in relation to the modelling of an automotive floor. More in detail, the aim of the paper is first to investigate what impact has the presence of the tunnel on the TL of a vehicle floor in bare and trimmed conditions and then to evaluate if the presence of the tunnel can be better modeled by using a semi-cylinder or three flat plates welded together in a trapezoidal shape, both shapes considered as a reasonable simplification of the actual geometry of a typical tunnel. The analysis is carried out at simulation level using FE. To investigate both air bone noise and structure borne noise transmission, two types of excitations are used: a diffuse acoustic pressure field applied to the entire floor surface and an imposed displacement applied to the edge of the floor surface. Furthermore, 3 different kind of trims are taken into consideration in order to analyze if and how the tunnel modeling strategy may influence the evaluation of the trim effectiveness.

Proton-conducting Ceramic Fuel Cells for Co-Producing Electricity and Fuel – A Design for Manufacture and Assembly (DFMA) Analysis

This work develops preliminary design for manufacture and assembly (DFMA) models of a novel, proton-conducting, anode-supported ceramic electrochemical cell for co-producing electricity and fuels simultaneously. These DFMA models can then be used to estimated future, expected costs incorporating the novel cell design under various manufacturing production scenarios. The cell electrochemically coverts oxygen (O2) in air and methane (CH4) fuel (the primary constituent of natural gas) into electricity, water, and higher-order hydrocarbons, such as ethane (C2H6). To do this, the cell integrates a methane coupling catalyst into the anode and thereby co-produces ethane (C2H6) and hydrogen (H2) at the anode. The ethane can then be converted into other fuels. The cell is part of a joint R&D effort by Argonne National Laboratory (ANL) and the Illinois Institute of Technology (IIT). The cell’s current technology readiness level (TRL) is about a one (1), i.e. laboratory-scale demonstration of the fundamental concept.Approach:Gaia Energy Research Institute (Gaia) collaborates closely with ANL and IIT to develop the DFMA models for this novel cell design. Gaia works closely with ANL and IIT to identify and analyze key electrochemical cell engineering performance data. Gaia then develops and deploys custom DFMA computer models and data sets. DFMA models center around the electrolyte-electrode assembly (EEA), or the ‘heart’ of the electrochemical cell, where the anode and cathode half-reactions occur. Gaia first develops a specific physical embodiment of the novel cell, then the cell’s bill of materials (BOM), and finally cost estimates for the electrochemical cell, fuel cell stack, and full-scale stationary fuel cell system. Gaia follows this methodology:1. Develop a specific design that physically embodies the EEA concept;2. Develop the EEA’s BOM to specify quantities of components and materials used;3. Identify, for all key materials, price quotes from one or more manufacturers;4. Calculate the minimum costs for the EEA based on materials costs alone;5. Ascertain the EEA’s primary cost drivers;6. Quantify the uninstalled capital costs for a full-size fuel cell stack and stationary fuel cell system incorporating the novel cell design.With the exception of the EEA, other parts of the fuel cell, stack, and system were assumed to be somewhat similar in design to more traditional stationary solid oxide fuel cell (SOFC) systems. Capital costs for the novel stack design were scaled linearly with stack power density. This work estimates stack and system costs for a 100 kWe net electric stack mass-produced at a rate of 50,000 systems per year.Results:Model results indicate that the fuel cell stack subsystem will cost about $478/kW and the entire fuel cell system will cost about $597/kW, including all BOP components. These stack costs are roughly 74% higher than a ‘plain vanilla’ SOFC subsystem, analyzed by the author for DOE in a prior analysis. These system costs are roughly 48% higher than the same ‘plain vanilla’ SOFC system previously analyzed. At the same time, these cost estimates are well below the DOE ARPA-E program goal of < $2,000/kW.Gaia observed an order of magnitude difference in price quotes for several of the specialty ceramic materials investigated. Price quotes from Praxair Specialty Ceramics were approximately double those of Trans-Tech Inc. The reasons cited for the extreme price differential were different manufacturing methods, specifically a chemical co-processing approach for Praxair and a solid-state material manufacturing process (SSMP) for Trans-Tech Inc. The pros and cons of each manufacturing approach are discussed in greater detail in this talk. This analysis assumes that SSMP is used with no degradation in cell performance and bases subsequent cost estimates solely on prices from Trans-Tech Inc., and not Praxair, at ANL’s request.The primary cost driver for the EEA appears to be the BZY-NiO anode substrate. The BZY and NiO anode substrate material is estimated to cost either 2.88 cents/cm2 [based on price quotes for BZY from TransTech Inc.] or 16.40 cents/cm2 [based on price quotes from Praxair Specialty Ceramics]. If the lower BZY cost estimate is taken based on price quotes from Trans-Tech Inc., 52% of the cost derives from the BZY. If the higher BZY cost estimate is taken based on price quotes from Praxair Specialty Ceramics Inc., 92% of the cost derives from the BZY. The secondary cost driver for the EEA appears to be the anode catalyst. The catalyst material is estimated to cost 2.45 cents/cm2. 94% of its cost is due to the material cost of the platinum. The EEA is estimated to cost 5.56 cents/cm2 or $278/kW of gross electric power from the cell or stack.

A Scheduling Algorithm for Multi-Workshop Production Based on BOM and Process Route

For the scheduling problem of complex products in multi-workshop production, this paper studied the BOM (Bill of Materials) structure of complex products and the characteristics of the process route and developed the construction method of a multi-level process network diagram. Based on this, a comprehensive mathematical model for scheduling on multi-workshop production was proposed. An improved particle swarm algorithm (PSO) was proposed to solve the problem. By constructing the network subgraph, the invalid search path of the algorithm was avoided, and the efficiency of the algorithm was improved. In addition, for the scheduling problem with product time constraints, this paper presented a path search rescheduling strategy to ensure that the algorithm could obtain an effective search path. Finally, the model and algorithm were verified through a case study. This paper optimized the parameters of the algorithm by different tests and obtained the optimal range of the parameters. At the same time, through the analysis of the scheduling of complex products in a multi-workshop environment, the effectiveness and practicability of the above methods were verified.

Introducing electronic circuits and hydrological models to postsecondary physical geography and environmental science students: systems science, circuit theory, construction, and calibration

Abstract. 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.

CAD와 BOM 통합 데이터베이스 기반 로봇 조립 계획 시스템 아키텍처 개발

This study proposes a system architecture based on integrated Computer-Aided Design (CAD) and Bill of Material (BOM) databases for a robot assembly planning system. The architecture consists of CAD, Product Data Management (PDM) and robot assembly planning applications based on CAD, BOM and robot databases. It manages shape and product structure data from 3D CAD files as data objects in CAD and BOM databases, and stores general robot assembly planning data from robot teaching results as robot path objects in the robot database. Robot engineers create robot assembly plans using a process BOM that incorporates data from the CAD, BOM and robot databases. Throughout the generation of robot assembly plans, the architecture uses the shape data of participating parts in CAD database to automatically calculate the positions of robot end-effectors. This paper describes the implementation of applications and databases in the architecture using FreeCAD, MariaDB and Apache Tomcat Web application server. It also outlines cases of experimental robot assembly planning using the implemented planning systems and robot arms at laboratory level.

Integrated lot sizing and blending problems

The standard blending problem consists of combining components to produce a final product with a given demand, while satisfying specific criteria with respect to the global blend and minimizing the total cost. The Bill-Of-Material (BOM) (or recipe) indicates which components are used and in which proportion. Typically, there is some flexibility in the planning process with respect to the proportion used for each of the components, where it may vary between a minimum and a maximum level instead of being fixed. This problem has been widely studied in a single period setting. However, the problem becomes more complex when we take into account a longer time frame. In such a case, demand for the final product occurs in several time periods, and both the final product and the components can be held in stock. In the integrated lot sizing and blending problem, the decisions relate to the production of the final product via the blending process, and the production (or procurement) of the components over an extended time horizon. We propose three mathematical formulations for this integrated problem and present a theoretical analysis of their Linear Programming relaxation bounds. In a computational experiment, we analyse the impact of important parameters such as the level of flexibility in the BOM, the variance in the procurement cost among the components, and the variance of the proportion of the components in the total mix. Furthermore, we analyse the value of integration by comparing the solution of the integrated models to the solutions of approaches that do not fully capture this integration such as a lot-for-lot approach, just-in-time models without inventory for the final product or components, and a hierarchical approach.

Flexible architecture for real-time synchronized processing of multimedia signals

Simultaneous processing of multiple video sources requires each pixel in a frame from a video source to be processed synchronously with the pixels at the same spatial positions in corresponding frames from the other video sources. However, simultaneous processing is challenging as corresponding frames from different video signals provided by multiple sources have time-varying delay because of the electrical and mechanical restrictions inside the video sources hardware that cause deviation in the corresponding frame rates. Researchers overcome the aforementioned challenges either by utilizing ready-made video processing systems or designing and implementing a custom system tailored to their specific application. These video processing systems lack flexibility in handling different applications requirements such as the required number of video sources and outputs, video standards, or frame rates of the input/output videos. In this paper, we present a design for a flexible simultaneous video processing architecture that is suitable for various applications. The proposed architecture is upgradeable to deal with multiple video standards, scalable to process/produce a variable number of input/output videos, and compatible with most video processors. Moreover, we present in details the analog/digital mixed-signals and power distribution considerations used in designing the proposed architecture. As a case study application of the proposed flexible architecture, we utilized the architecture for a realization of a simultaneous video processing system that performs video fusion from visible and near-infrared video sources in real time. We make available the source files of the hardware design along with the bill of material (BOM) of the case study to be a reference for researchers who intend to design and implement simultaneous multi-video processing systems.

Prototypes for automating product system model assembly.

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). 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. 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. 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. 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.

Automating CAD for creating assembly structure from Bill of Materials

This paper presents the development of an add-on for CAD system generating assembly structure automatically based on a given Bill of Materials (BOM). The BOM in Excel format is scanned by the system and the system arrange 3D CAD files into assembly at in CATIA V5 CAD system automatically. This program has been tested and succeeded well at compiling 3D assembly based on 3D part file data that is available or not available. If the 3D file is not available then the 3D assembly is still generated according to the assembly structure listed on Excel file but its 3D representation does not appear.

Optimisation of the Automated buffer positioning model under DDMRP logic

Abstract This paper discusses the buffer positioning problem in a hybrid Make-To-Order/Make-To-Stock (MTO/MTS) setting with deterministic lead times. With a more demanding market, delivery times have become more competitive. A dynamic amount of inventory is made immediately available at certain points of the manufacturing process, including the final product, allowing to improve the flow of materials and meet more competitive deadlines. This work is particularly interested in optimizing buffer positioning in the context of Demand Driven Material Requirement Planning (DDMRP), where the decision maker can process the location and the sizing of the inventory buffers in complex Bills of materials (BOMs) in the most efficient strategy all while minimizing inventory costs under service time constraint. To do so, an improvement of the existing model of the two first steps of DDMRP: the strategic inventory positioning and calculating the buffer levels, is proposed. A linearization of the model and better solutions in shorter computational times compared to the literature are given by the enhanced model which is proven through various simulations. A cost objective function was evaluated in this model, and was solved using CPLEX and its CP Optimizer. These simulations would prove a better and more efficient approach for an enhanced DDMRP implementation.

Optimizing Assemble-to-Order Systems: Decomposition Heuristics and Scalable Algorithms

We consider continuous-review assemble-to-order (ATO) systems with a general bill of materials (BOM) and general leadtimes. ATO systems have the advantage of mass customization and are widely adopted in practice. However, characterizing the optimal inventory policy is notoriously challenging and computational intractable, especially in large-scale systems. We propose effective and computational scalable heuristics through asymptotics, sample-path, linear programming and primal-dual analyses. First, we characterize the asymptotically optimal policy for the M-system. The policy consists of a periodic review priority (PRP) allocation rule and a coordinated base-stock (CBS) replenishment policy. We then construct heuristic policies using insights from the asymptotically optimal policy. In particular, we adopt the PRP allocation rule and develop a decomposition approach for inventory replenishment. This approach decomposes a general system into assembly subsystems and a linear program is constructed to compute policy parameters. However, both the CBS and the assembly decomposition approach are limited to simple systems. We then consider a second approach, which decomposes a system into distribution subsystems and each subsystem has a straightforward solution, which is similar to the newsvendor problem. We use the primal-dual analysis to show that the expected cost under the optimal independent base-stock policy in a general system could be bounded by two newsvendor systems with properly set parameters. Finally, we examine the effectiveness and scalability of these two decomposition approaches in numerical tests. We find that the assembly decomposition is very effective but computationally expensive and thus only good for small-scale systems; the distribution decomposition performs as effective as the optimal independent base-stock (IBS) policy, but is highly scalable for large-scale systems. Numerical tests also provide some interesting insights on the impact of system parameters on the value of past demand information.

퍼지 베이지안 네트워크와 증거 이론을 이용한 FTA-FMEA 통합시스템에 의한 오류진단

Purpose This study presents a combined model of Fault Tree Analysis (FTA) and Failure Mode and Effects Analysis (FMEA) using evidence theory and Fuzzy Bayesian Network (FBN) under uncertain circumstances which are caused by the presence of incompleteness, randomness and ambiguity of failure modes. Methods In order to identify the critical failure modes according to the multi-level FTA-FMEA, the Trapezoidal Distribution-Type Basic Belief Assignment (TrDTBBA) is used to consider the viewpoints of experts and to resolve the conflicts of evidence The proposed FTA-FMEA-FBN model derives fuzzy posterior probabilities to implement fault diagnosis approach which is more suitable than fuzzy prior probabilities when conducting qualitative reasoning of vague probability. Results A novel method for identifying the critical failure modes according to the level of hierarchical Bill of Material (BOM) is based on the proposed FTA-FMEA-FBN integrated model that illustrates chassis system consisting of 6 components, 4 modules and 6 parts. Conclusion This suggested FTA-FMEA-FBN model is convenient for a risk evaluation in the following uncertain circumstances: 1) The information of failure modes are incomplete, 2) The numbers of failure modes comprised of three levels are too abundant, 3) The probabilities of failure modes have a lack of quantification data. The fusion strategy of those three risk techniques implements computational efficiency and provides a synergistic effect to accurately identify the critical failure modes under uncertain circumstances.

Development of Distributed MRP System for Production Planning and Operation in Korean OEM/ODM Cosmetics Manufacturing Company

Up to date cosmetic OEM/ODM (original equipment manufacturing/original development manufacturing) industry receives attention as a future growth engine due to steady growth. However, because of limited research and development capability, many companies have employed commercial management platforms specialized for large-sized companies; thus, overall system effectiveness and efficiency is low. Especially, MRP (material requirement planning) system introduced originally in 1970s is employed to calculate the requirement of the parts. However, dynamic nature of production lead time usually results in incorrect requirements. In addition, its algorithm does not consider the capability of the production resources. Also, because the commercial MRP system calculates all subcomponent for fixed period, the more goods have subcomponent, the slower calculation is. Therefore, conventional MRP system cannot respond complicated situation in time. In this study, we will suggest a new method that can respond to complicated situations resulting from short lead time and urgent production order in Korean cosmetic market. In particular, a distributed MRP system is proposed, that consists of multi-functional and operational modules, based on the characteristic of the BOM (bill of material). The distributed MRP system divides components (i.e. products and parts) into several fields and decrease the problem size; thus, we can respond to dynamically changed data any time. Through this solution, we can order components quickly, adjust schedules and planned quantity, and manage stocks reasonably. In addition, a prototype of the distributed MRP system is presented in this paper, in which ERP (enterprise resource planning) sever data is associated with an excel spreadsheet via MSsql. System user interface is implemented by a VBA (visual basic for applications) tool. According to a case study, response rate for delivery and planning achievement rate were enhanced about 20%, and inventory turnover was also decreased. Consequently, the proposed system improves overall profit.

Research on Spent LiFePO4 Electric Vehicle Battery Disposal and Its Life Cycle Inventory Collection in China.

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.

Digital Twin Conceptual Model within the Context of Internet of Things

As the Internet of Things (IoT) is gaining ground and becoming increasingly popular in smart city applications such as smart energy, smart buildings, smart factories, smart transportation, smart farming, and smart healthcare, the digital twin concept is evolving as complementary to its counter physical part. While an object is on the move, its operational and surrounding environmental parameters are collected by an edge computing device for local decision. A virtual replica of such object (digital twin) is based in the cloud computing platform and hosts the real-time physical object data, 2D and 3D models, historical data, and bill of materials (BOM) for further processing, analytics, and visualization. This paper proposes an end-to-end digital twin conceptual model that represents its complementary physical object from the ground to the cloud. The paper presents the proposed digital twin model’s multi-layers, namely, physical, communication, virtual space, data analytic and visualization, and application as well as the overlapping security layer. The hardware and software technologies that are used in building such a model will be explained in detail. A use case will be presented to show how the layers collect, exchange, and process the physical object data from the ground to the cloud.

Workload Balancing for Production Planning With Lot Streaming and Multilevel BOM

This article addresses a real-world tactical production planning problem in which a series of real-world constraints need to be considered, such as no backorder, products with multilevel bills of material (BOMs), and lot streaming production. Under the premise of no backorder, the objective of this plan is to make the workload as balanced as possible throughout the planning horizon. An integer quadratic programming model is first proposed to formulate this problem. Then, based on the analysis of the optimal solution for a common BOM structure, this problem is reformulated to a simplified problem where only one item in BOM needs to be considered. Some optimality properties are further derived to help solve this problem. An enhanced variable neighborhood search algorithm is developed to solve this problem, and a lower bound is put forward to measure the performance of the algorithm. Experimental results show that this algorithm can obtain high-quality solutions in a short time. Note to Practitioners —Effective and intelligent decisions about production planning could have a significant influence on the performance of the manufacturer. This article is motivated by a tactical production planning problem that we encounter in a factory producing discrete equipment. A production plan needs to be made with the consideration of various realistic characteristics in this factory. Without delaying the orders, the objective of the plan is to balance the workload throughout the planning horizon. Currently, the planners make the production plan manually based on their experience in Microsoft Excel. Due to the complexity of this problem and the increasing number of orders, it is difficult and burdensome for planners to make a high-quality production plan manually. In this article, a mathematical model is proposed to formulate this problem, and some theoretical properties are derived to help solve this problem. An enhanced variable neighborhood search-based algorithm is proposed to solve large-scale problems, which could provide a more detailed plan than the current plan. This study could ease the planner from burdensome planning work, improve the quality of the production plan significantly, and be adapted to solve planning problems with similar production characteristics and objectives. In the future, more production characteristics will be considered to meet the diversified demands of production planning.

NB-IoT and GNSS All-In-One System-On-Chip Integrating RF Transceiver, 23-dBm CMOS Power Amplifier, Power Management Unit, and Clock Management System for Low Cost Solution

This article presents a fully integrated stand-alone narrowband Internet-of-Things (NB-IoT) and global navigation satellite system (GNSS) system-on-chip (SoC). It aims for an all-in-one system to integrate all necessary blocks such as an RF transceiver, a power management system (PMIP), and a clock management system and to save a bills-of-material (BOM) cost. An RF transceiver is integrated to support multi-band cellular IoT and GNSS with a CMOS RF power amplifier transmitting 23-dBm output power. A PMIP, including bucks, a boost, and low-dropout regulators (LDOs), is integrated to support coin cell or AAA battery and to support a wide input supply voltage range from 2.5 to 5 V. In addition, clock management system is embedded with a digitally controlled crystal oscillator (DCXO), a relaxation oscillator (RCO), and temperature sensor units (TSUs). It is fabricated in a standard 28-nm CMOS process and its size is 24.6 mm2. The power consumption of always-on-block is 15 $\mu \text{W}$ , and the sleep current consumption is less than 10 $\mu \text{A}$ at 3.8 V.

Disassembly-based bill of materials data for consumer electronic products

Consumer electronic products have a complex life cycle, characterized by environmental, social, and economic impacts and benefits associated with their manufacturing, use, and disposal at end-of-life. Accurately analysing these trade-offs and creating sustainable solutions requires data about the materials and components that make up these devices. Such information is rarely disclosed by manufacturers and only exists in the open literature in disparate case study format. This study presents a comprehensive database of bill of material (BOM) data describing the mass of major materials and components contained in 95 unique consumer electronic products. Data are generated by product disassembly and physical characterization and then validated against external benchmarks in the literature. The study also contributes a reproducible framework for organizing BOM data so that they can be expanded as new products enter the market. These data will benefit researchers studying all aspects of electronics and sustainability, including material scarcity, product design, environmental life cycle assessment, electronic waste policy, and environmental health and safety.

A Process-Based Modeling Method for Describing Production Processes of Ship Block Assembly Planning

Ship block assembly planning is very complex due to the various activities and characteristics of ship production. Therefore, competitiveness in the shipbuilding industry depends on how well a company operates its ship block assembly plan. Many shipbuilders are implementing various studies to improve their competitiveness in ship block assembly planning, specifically regarding technology usage, such as modeling and simulation (M&amp;S) and Cyber-Physical Systems (CPS). Although these technologies are successfully applied in some production planning systems, it is difficult to tailor ship production planning systems with flexibility due to unexpected situations. Providing a flexible plan for these production planning systems requires a way to describe and review the organic relationships of ship production processes. In this research, a process-based modeling (PBM) method proposes a novel approach to describing the production process of ship block assembly planning by redefining production information based on changing instructions. The proposed method consists of four modeling steps. The first creates a unit model, which includes the products, processes, and resource information for the block. The second designs an integrated network process for linking unit models according to the bill of materials (BOM). The third creates a process-based model that describes the production processes by combining unit models. The fourth generates a simulation model by applying a Petri-net to the process-based model, which analyzes the productivity of the ship’s block assembly processes. PBM identifies the assembly process’ interrelationship and shows that productivity can be reviewed to uncover ship production problems.