Integration of measurement data in the comprehensive modelling approach

A product redesign strategy can effectively shorten design lead time and reduce the manufacturing cost of innovative development for the manufacturing industry to stay competitive. Identification of function components is the basis of product redesign. Existing practices to identify the critical component and customer requirements are considered while complaint and historical failure data, crucial for improving product reliability, are frequently ignored. The objective of the article is to develop an integrated framework of product redesign and innovation considering customer requirements and product failure modes. The novel framework integrates the design for manufacturing and assembly (DFMA) and design for reliability (DFR) approaches, as well as finite element analysis to address the cost reduction of product redesign at early-stage, reliability improvement, and higher customer satisfaction. The proposed integrated framework is validated using an example of an Indonesian SME’s cooking stove. The redesigned cooking stove showed substantial improvements with 5.46% cost reductions, 20.32% design efficiency, and an 52.81% safety factor.

The principal goal of an integrated circuit DFM (design for manufacturing) initiative is to insure arrival at electrical circuit designs and packaged IC components which are inherently producible within the manufacturing environment. In order to achieve this objective the component design must, from early in the product concept phase, incorporate a full range of manufacturing production constraints and considerations. DFM not only implies designing for physical product fabrication but also must include design for testability, design for assembly or packaging, design for reliability and integration, and networking of all these areas. The key to the success of a DFM program lies in increased accuracy in the modeling of the process and product designs, product simulations, and effective manufacturing feedback of key parametric data. Factory fabrication efficiency increases as the design accuracy and tolerances increase. Statistically valid models, extracted from and representative of the controlled process, can be fed back to product designers via advanced CAD/CAM/CAE integrated systems, thus reducing design cycle times by limiting the design space to be explored in order to achieve a predetermined product yield.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

The concept of concurrent engineering (CE) has changed the traditional process of design to an integrated process, comprising all aspects of design, manufacturing, costing, process control etc. In composite product development, CE is adopted to enhance quality, to reduce time of production, and to reduce cost. There have been several models that consider design for minimal weight, design for cost, design for quality, design for manufacture, design for reliability, design for metal inserts, design for environment etc., separately for composite product development. In the present paper, we apply the graph theoretic approach to DFX analysis methodology for design of composite products. The DFX methodology is new to composite design, and is applied to study the various DFX components, like design for cost (DFC), design for manufacture (DFM), and design for minimal weight (DFMW), simultaneously. In this study, an example for development of fiber reinforced polymer composite (FRP) drive shafts is taken up. Several material combinations like E-glass/epoxy, E-glass/polyester, and HM-carbon/epoxy composite materials are compared in light of their performance with conventional steel material. The concurrent graph theoretic approach with a permanent function is used to account for the interdependencies existing among the design parameters in studying DFMW, DFM, and DFC.

The unique tool-less and layer-upon-layer capabilities of additive manufacturing (AM) have largely lessened manufacturing constraints and significantly broadened design freedom. AM offers new opportunities for developing customized products by achieving significant improvements in product performances and lower overall costs. The AM-enabled customization opportunities inevitably challenge traditionally design theories and methodologies (DTMs) that lack design knowledge for AM products. Here, to counteract this limitation, this study presents a novel methodology for constructing knowledge supporting DTMs for AM-enabled customization: customized design for AM (CDfAM). The CDfAM supports two main phases of design for additive manufacturing (DfAM): (1) opportunistic DfAM in a conceptual design phase and (2) restrictive DfAM in an embodiment design phase. In terms of the knowledge construction for the opportunistic DfAM, it is essential to construct knowledge that supports to explore a customized design space enabled by AM’s design freedom from the conceptual design phase. To address the challenge, this study provides a novel method for capturing knowledge of customized AM product behaviors. First, this study proposes an affordance-based DfAM framework by integrating the concept of affordance into three link chain models. Second, an affordance structure is proposed to develop a formal method for representing the knowledge of the customized AM product behaviors utilizing finite state automata. In terms of the knowledge construction for the restrictive DfAM, this study presents a formal method for representing and reasoning customizable modular knowledge of design rules for AM. First, a novel structured modular hierarchy and associated formalisms of AM design rule elements are presented. Second, machine learning is employed to automatically learn design rules from AM data, which leverages the proposed design rule formalisms. A knowledge graph is designed and built to demonstrate the proposed methodology. Case studies with AM products such as a transtibial prosthesis leg and AM data such as ex-situ AM measurement data provide illustrations in this study. The case studies show that the proposed methodology explicitly constructs structured and correlated AM design knowledge of customized AM product behaviors, product geometries, and additive manufacturability constraints. It is also shown that qualified design knowledge in the knowledge graph enhances automation of DfAM decision-making and data-driven knowledge constructions. The proposed CDfAM methodology enables incorporating both customized AM product functionalities and additive manufacturability constraints into product designs. This study provides a foundation for AM knowledge construction and data- and knowledge-driven automation of DfAM decision-making. Validated design rules and representations are expected to contribute to developing international standards on AM design rules.

In this paper we present a systematic approach to identify, predict and optimize design process interaction (DPI); and to co-optimize holistically from technology to chip/system. This has enabled the best performance, power and yield for GPU/SOC for high performance computing (HPC), artificial intelligence (AI) and autonomous vehicles applications. GPU HPC improved 100× in past 10 years, more than Moore's Law. AI deep learning performance has improved even faster, by ∼100× in 5 years, enabled by co-optimizations in architecture, circuit, and process technology. The era of defects per trillion (DPPT) level of perfection has also arrived. DPPT criteria for defect and variability outlier control is required to meet yield and reliability for today's complex GPU with 100s of billions of layout pieces. Intelligent test chip designs are employed to identify issues and margins, to help predict large chip and high-volume issues with smart sample learning. TCAD defect/reliability margin modeling, design for manufacturing (DFM), design for reliability (DFR), are also used to optimize design and process, to maximize PPAYRT (power, performance, area, yield, reliability, time to market).

Design for Manufacturing (DFM) and Design for Reliability (DFR) are important measure to verify and increase a product's manufacturability and reliability. This assessment can be achieved with Critical Area Analysis (CAA). In this study, the CAA results are correlated to the reliability data in terms of Defect Per Million (DPM) derived from the number of customer's field return units. Our differentiator approach was to analyze the defects and the hot spot location of the failed unit, and map the location to the CAA heat map to investigate if the failure locations fall in the critical area. The analysis was performed on products with high DPM rate. This paper shows some of the mapping examples and the outcome indicated > 50% Back End of Line (BEOL) failure can be potentially avoided upfront in layout design.

The design of parts and manufacturing systems can be viewed from different perspectives. This paper discusses the design of parts and manufacturing systems from reliability and maintainability perspectives. A convenient method of considering reliability and maintainability is through the use of design rules which are based on empirical and theoretical knowledge. Four design rules for improvement of reliability and maintainability of systems are presented. The design rules are proven and substantiated with numerical results. The relationship between the design for reliability and maintainability rules and design for manufacturing process rules is discussed.

Under Photovoltaic Manufacturing Technology (PVMaT) 4A1, Ascension Technology (AT) is developing the SunSine300 AC PV module. AT`s goals in this project are to meet Underwriters Laboratory (UL) 1741 requirements, obtain Federal Communications Commission (FCC) Class B verification, complete the AC module system design and development, advance the inverter design, design for manufacture, design for reliability, design for serviceability, and demonstrate commercialization through production and sale of about 100 units. To meet these goals, AT corrected a number of deficiencies identified by UL`s preliminary investigation before proceeding to the full UL investigation; a SunSine300 prototype was tested and found to comply with FCC Class B requirements; AT designed a complete line of balance-of-systems hardware for the SunSine 300; AT`s design and performance advancements include accomplishing a total harmonic distortion drop from 5% to 2%, devising a method to eliminate false detection of zero crossings that could damage the inverter, improving the anti-islanding with the addition of AT`s proprietary ZEBRA technique, and redesigning the enclosure for thermal performance, manufacturability, and UL and FCC approval; performing extensive testing in Phase 2 to discover failure modes and susceptibility to aging; and designing the SunSine300 to be easily and safely serviced. 3 figs., 3 tabs.

Purpose – The purpose of this paper is to present Design Rules for additive manufacturing and a method for their development. Design/methodology/approach – First, a process-independent method for the development of Design Rules was worked out. Therefore, geometrical standard elements and attributes that characterize the elements’ shapes have been defined. Next, the standard elements have been manufactured with different attribute values with Laser Sintering, Laser Melting and Fused Deposition Modeling, and their geometrical quality was examined. From the results, Design Rules for additive manufacturing were derived and summarized in a catalogue. Findings – Due to the process independent method, Design Rules were developed that apply for the different considered additive manufacturing technologies equally. These Design Rules are completely function-independent and easily transferable to individual part designs. Research limitations/implications – The developed Design Rules can only apply for the considered boundary conditions. To extend the Design Rules’ validity, their applicability should be proven for other boundary conditions. Practical implications – The developed Design Rules practically support the design of technical parts. Additionally they can be used for training and teaching in the field of “design for additive manufacturing”. Originality/value – The developed Design Rules constitute a first step toward general Design Rules for Additive Manufacturing. Thus, they might form a suitable basis for further scientific approaches, and the Design Rules can be used to set up teaching documentations for lessons and seminars.

To optimize the performance of organic light-emission devices (OLEDs), optical simulation or electrical simulation is often used to help designing the device structures. However, employing electrical or optical simulation separately to optimize the device might lead to incorrect conclusions. A few researches have combined optical and electrical simulations to design OLED structures by merely inserting the maximum carrier recombination rate calculated from electrical simulation into optical simulation programs, which is still insufficient for optimization of OLEDs due to lack of considering the influence of optical interference positions. In this paper, we investigate the OLED performance by using three simulation methods, pure optical, pure electrical, or combination of both, to design the devices. Using the models incorporating both electrical and optical simulations, we found that the optimal emission position occurs neither at the place with the best optical interference nor at the point where carrier recombination rate is the maximum. In order to verify the simulation results, we design the testing devices, red fluorescence OLEDs of bi-layer structures, with various positions of recombination emission. It is found that the position of recombination emission has major impact on the device performance of OLEDs, which lead to some important design rules. With integration of electrical and optical simulations, the real emission position could be predicted with excellent agreements to the experimental results. Applying this method to design the red fluorescent bi-layer OLEDs, the device with very high efficiency of 8.44 cd/A was achieved.

The Design for Manufacturability (DFM) Process is the most critical process in determining if a particular product will achieve its quality, cost, performance, and time to market goals. With the increasing trends to outsource the assembly of electronic products, the gap between the product development organization and the product manufacturing organization is continuing to increase both geographically and organizationally. Design for Manufacturability must include a detailed understanding of the processes that will be used to build the product, how the processes are developed, how the processes are controlled, and how continuous improvement is accomplished. The vast majority of electronic product development companies practice some form of DFM. The organizations with good design for manufacturability systems understand that manufacturing issues must be considered as early in the product design process as possible. Although it is generally agreed that DFM is critical to an optimized product development process there is no universal agreement on the definition of DFM, the approach, procedures, and methods used, and exactly what the key factors of a DFM system are. All product development organizations use sophisticated computer aided design (CAD) tools to design their products. These tools have the capability to insure most of the “nuts and bolts” design rules and guidelines are adhered too. Factors such as component pad size, component spacing, board edge clearance, fidcuial size number and location, etc. are built into the CAD design tool. These factors are critical to the manufacturability of a printed circuit board design. However, DFM is much more than insuring the printed circuit board design rules are obeyed. This paper will attempt to define Design for Manufacturability and discuss several of the key factors in the DFM Process

Summary Time depth conversion, commonplace in the geophysical workflow, is the key link between interpretive work in time and geological representation in depth. Often, the uncertainty between trying to place time values in depth has been a challenge to capture as it requires thorough study and also careful consideration of all input data and parameters. Whether the outcome of depth outputs is to produce realistic maps or to aid in well placement, there is essential need in being able to quantify this through comprehensive velocity modelling methods. This paper describes the use of scenario based modelling that is combined with geostatistical applications for a brown field development in offshore Malaysia. This is an attempt to capture uncertainty in time to depth conversion and possible cases extensively. Having been in production for more than 30 years, optimizing the value provided by newly acquired 3D broadband seismic and vertical seismic profile (VSP) would allow for improved de-risking when coupled with this comprehensive velocity modelling approach. Three velocity models were built based through varying input data available to cover a spectrum of possible scenarios. Gross rock volume (GRV) calculations from each model were then subjected to a Monte Carlo Simulation based on the respective parameters. Comparison of the GRV from each of the model’s multiple realization illustrates how this hybrid approach proved to be successful in capturing the uncertainty range sufficiently for depth conversion. Due to successful integration of new data and these approaches, it improved understanding of structural uncertainty for reservoir modelling.

The design for manufacturability (DFM) method is most effective when integrated with the new product development (NPD) process. Due to the focused nature of the associated product and process knowledge and the extensive effort required, there are many NPD situations where classical DFM techniques cannot be readily applied. In this paper, Pro-DFM a multi-criteria model for manufacturability analysis that identifies product realisation opportunities (PRO) for cost reduction is presented. The key assumption in Pro-DFM is that the NPD team has a baseline estimate of production costs, and the evaluation question is how DFM issues will affect the expected unit production cost. The Pro-DFM model analyses a new design in three different factors: part procurement and handling, product assembly fabrication processes, and inventory costs. Each of these is independently analysed using a hierarchy of multiple criteria and sub-criteria. This approach is found to be amenable to most NPD processes, and conducive to easy integration. Each evaluation sub-criterion is presented in the form of a simple query, which is associated with a set of responses that is flexibly anchored to a uni-dimensional scale. A case study example is used to demonstrate the DFM evaluation process and the derivation of the cost penalties.

Die cracking and interfacial delamination are of major failure modes in IC packages. To these crack-related problems, design approaches based on traditional strength theories, are inadequate and insufficient. To achieve a more reliable and robust design, a fracture mechanics approach is needed. In this paper, fracture mechanics is applied to flip chip BGA design, assumed that the major potential failure mode is cracking of die from its backside. Fracture mechanics is integrated with the finite element analysis (FEA) and design of virtual experiments to analyze the effects of location and length of a die crack, and the effects of some key material properties and package dimensions on flip chip BGA reliability in terms of die cracking. The stress intensity factor and the strain energy release rate, are used as the design indices. The FEA is used as a numerical tool to calculate the fracture parameters. And the virtual DOE is employed to determine contributions of each design parameters to die cracking and their acceptable design windows. The investigation consists of three parts. The first is relations of length and location of a die crack with the fracture parameters. The relations are established through sweeping along crack length for a crack located in the center of die backside, and along the die backside surface. The critical crack length is determined. The second is the virtual DOE based on fracture mechanics. Several key material properties and cracking are calculated. From it, some generic design guidelines are made. The third part compares the virtual DOE design results between using the maximum normal stress (MNS) theory and using the fracture mechanics approach. The comparison gives a clear picture of the applicable range of the MNS theory. It is concluded that design optimization be a must in order to achieve a robust package design. Substrate and die thicknesses are the two most significant factors to die cracking of flip chip BGA. Increasing substrate thickness and reducing die thickness are the most effective measures to design a package with high resistance to die cracking. The fracture mechanics approach will produce more accurate design result than the MNS theory.

In the race of miniaturization, manufacturers of automotive devices always require smaller electronic components. To save space and in the same time improve performances, some sensors are placed directly ‘Under the hood’ and are directly exposed to harsh environment, such as braking systems, oil, exhaust gaz, cooling liquids and so on. These requirements drive the increasing demand for reliable capacitors that can withstand temperatures up to 200°C. Murata has developed a unique capacitor technology in silicon as well as integrated passive devices based on 3D trenches with high aspect ratio. This paper reports the reliability of automotive grade silicon capacitors for high temperature applications up to 200°C. The development of a range of Silicon capacitors, with an operating temperature from -55°C up to +200°C will be presented here. The manufacturing process optimizations and the design rules (Design for Reliability) implemented to prevent failure mechanisms when exposed to such a high temperature will be described. The solutions to avoid top to bottom metal short (TBMS), electromigration (EM), intermetallic compound formation (IMC) and to enhance time-dependent dielectric breakdown (TDDB) will be depicted. The products have been qualified according to automotive electronic standard AEC-Q100, but exceeding by 65°C the grade 0, which is defined as the most severe conditions of the standard. The results of the reliability qualification both at wafer level and product level will be presented in details. The long-term stability of key electrical parameters of the Silicon capacitors is a main differentiator versus standard capacitor technologies for the ‘under the hood’ automotive market.