Efficient Fault Isolation and Failure Analysis Methods to Root Cause Defects in Microprocessors

In this paper we show an efficient workflow that combines Magnetic Field Imaging (MFI) and Dual Beam Plasma Focused Ion Beam (DB-PFIB) for fast and efficient Fault Isolation and root cause analysis in 2.5/3D devices. The work proves MFI is the best method for Electric Fault Isolation (EFI) of short failures in 2.5/3D Through Silicon Via (TSV) triple stacked devices in a true non-destructive way by imaging the current path. To confirm the failing locations and to do Physical Failure Analysis (PFA), a DB-PFIB system was used for cross sectioning and volume analysis of the TSV structures and high resolution imaging of the identified defects. With a DB-PFIB, the fault is exposed and analyzed without any sample prep artifacts seen in mechanical polishing or laser preparation techniques and done in a considerably shorter amount of time than that required when using a traditional Gallium Focused Ion Beam (FIB).

SummaryThis paper proposes an integrated actuator and sensor active fault‐tolerant model predictive control scheme. In this scheme, fault detection is implemented by using a set‐valued observer, fault isolation (FI) is performed by set manipulations, and fault‐tolerant control is carried out through the design of a robust model predictive control law. In this paper, a set‐valued observer is used to passively complete the fault detection task, while FI is actively performed by making use of the constraint‐handling capability of robust model predictive control. The set‐valued observer is chosen to implement fault detection and isolation (FDI) because of its simple mathematical structure that is not affected by the type of faults such as sensor, actuator, and system‐structural faults. This means that only one set‐valued observer is needed to monitor all considered actuator and sensor statuses (health and fault) and to carry out the fault detection and isolation task instead of using a bank of observers (each observer matching a health/fault status). Furthermore, in the proposed scheme, the advantage of robust model predictive control is that it can effectively deal with system constraints, disturbances, and noises and allow to implement an active FI strategy, which can improve FI sensitivity when compared with the passive FI methods. Finally, a case study based on the well‐known two‐tank system is used to illustrate the effectiveness of the proposed fault‐tolerant model predictive control scheme. Copyright © 2016 John Wiley & Sons, Ltd.

Enhanced product yields, reduction in throughput time, improved cost-effectiveness and product quality are examples of benefits gained by delaying apoptotic cell death in bioreactors. To examine the effect on recombinant protein production, bcl-x(L) was overexpressed in a CHO cell line secreting humanized monoclonal antibody directed against the alpha1beta1 integrin. When cell lines overexpressing bcl-x(L) were compared to the parent, cell viability was increased by 20% and titers by 80%. Total viable cell densities were similar and specific productivities were enhanced by almost two-fold on scale-up to bioreactors. Comparison in a chemically defined media demonstrated an even greater sustained viability in bcl-x(L) expressing cells by 50% and up to 90% increase in titer with no impact on product quality. Caspase 3 activities were monitored as a marker for apoptotic cell death. In the presence of Bcl-x(L), caspase activities were reduced to background levels. The role of Bcl-x(L) in protecting cells from premature death was further examined in studies performed in the presence of NaBu, at concentrations known to trigger cell death. Results demonstrated that cells expressing bcl-x(L) retained 88% cell viability with >2 fold increase in titer. Bcl-x(L) was similarly overexpressed in a different CHO cell line producing a humanized mAb against the chemokine MCP1. Once again, production titer was increased by 80% and viability by 75%. Together the studies have shown that overexpression of bcl-x(L) in production cell lines was able to significantly increase the titer by enhancing both the specific activity and total cell viability while maintaining product quality.

In this paper, it is shown that the high automation level of the object-oriented modeling paradigm for physical systems can significantly rationalize the design procedure of fault detection and isolation (FDI) systems. Consequently, an object-oriented FDI method for complex engineering systems consisting of subsystems from different physical domains like mechatronic systems, commercial vehicles, and chemical process plants is developed. The mathematical composition of the objects corresponding to the subsystems results in a differential algebraic equation (DAE) that describes the overall system. This DAE is automatically analyzed and transferred into a set of residual generators that enable a two-stage FDI procedure for multiple fault modes.

ABSTRACTQuick and timely fault detection is of great importance in control systems reliability. Undetected faulty sensors could result in irreparable damages. Although fault detection and isolation (FDI) methods in control systems have received much attention in the last decade, these techniques have not been applied for some classes of nonlinear systems yet. This paper deals with the issues of sensor fault detection and isolation for a class of Lipschitz uncertain nonlinear system. By introducing a coordinate transformation matrix for states and output, the original system is first divided into two subsystems. The first subsystem is affected by uncertainty and disturbance. The second subsystem just has sensor faults. The nonlinear term is separated to linear and pure nonlinear parts. For fault detection, two sliding mode observers (SMO) are designed for the two subsystems. The stability condition is obtained based on the Lyapunov approach. The necessary matrices and parameters are obtained by solving the linear matrix inequality (LMI) problem. Furthermore, two sliding mode observers are designed for fault isolation. Finally, the effectiveness of the proposed approach is illustrated by simulation examples.

A general defect modelling and simulation-assisted approach for fault isolation in failure analysis

Sensor fault identification based on time-lagged PCA in dynamic processes

A new hierarchical method for fault detection, isolation, and identification of nonlinear systems with applications for in-orbit closed-loop controlled satellites is proposed where fault detection employs unscented Kalman filter and adaptive thresholds. Fault isolation employs multiple model approach in conjunction with Bayes’ probability theorem and adaptive window, and fault identification employs dual state/parameter estimation using unscented Kalman filter. Results show up to 97% success rate under comprehensive Monte Carlo simulations for transient abrupt faults in satellite actuators.

Today’s VUCA (Volatile, Uncertain, Complex and Ambiguous) world and the continuous search for new products and services requires companies to pursuing excellence and continuous improvement. This paper aims to describe a lean implementation project developed in a Portuguese cutlery SME. Action-research was adopted as research method. The production processes of the most representative products (spoons, forks and knives) were analyzed with adequate tools (e.g. VSM – value stream mapping – and indicators monitoring). The main problems identified were excess of inventory (of both finished products and WIP – work-in-process), and consequent long throughput times and low productivity. The root causes for those problems were investigated. Then, improvement proposals, involving the creation of a system to monitor and control production orders, the implementation of daily kaizen meetings, the redefinition of safety stocks and reorder point of finished products and the promotion of training and creation of work instructions regarding equipment setups, were developed and implemented to mitigate the identified problems. The implementations had quite positive impacts such as WIP reduction of 255 K€, 38.5% decrease in finished products stock, throughput time reduction from 17.3 to 4.6 days for spoons and forks, and from 12.4 to 6.8 days in the case of knives, and, finally, an overall productivity enhancement of 36.5%.KeywordsLean manufacturingLean toolsContinuous improvementCutlery industry

A new method of diagnostic row reasoning based on trivalent residuals

This paper deals with the fault detection, diagnosis and control problems of time delay systems by designing a disturbance observer (DOB). In proposed method, the DOB estimates the changes occurred as an input disturbance. In fact, the DOB is implemented as a residual generator for the system. Subsequently, the estimated changes can be used to compensate the effect of faults and plant alterations directly. In this method, the estimated disturbances can be used for the FDI purpose and the final system would be fault tolerant, without the need to have all other faults isolable and identifiable. It provides a simple, low cost and effective fault detection and isolation method which can be applied to more practical systems. The applicability and effectiveness of the proposed method is illustrated by the simulations provided for an industrial water pressure control system which is supposed to be subject to faults.

A data-driven fault isolation and estimation approach for unknown linear systems

In the field of multivariate statistical process monitoring (MSPM), fault isolation has attracted increasing attention, due to its importance in ensuring process reliability and product quality. However, the existing fault isolation methods are mostly limited to linear settings with single variable isolation. For nonlinear modeling, the kernel method is commonly used, but the time for solving a kernel matrix and its storage required in the traditional method increase sharply with large sample size. To solve these issues, a multivariate fault isolation method based on accelerated kernel canonical correlation analysis (AKCCA) is proposed. In the new method, kernel canonical correlation analysis is utilized to associate variables with process anomaly and extracting nonlinear structures. Furthermore, full rank factorization is embedded in kernel matrix approximation while performing eigenvalue decomposition (EVD), which substantially reduces the storage and computational expense. In addition, faulty relevance of each variable is newly calculated, which improves the accuracy of fault isolation for nonlinear processes. The feasibility of AKCCA and its computational advantage are illustrated by a numerical case and the Tennessee Eastman benchmark.

Quantitative analysis of estradiol and six other steroid hormones in human saliva using a high throughput liquid chromatography–tandem mass spectrometry assay

We analyze gut architectures of 42 species of marine polychaetes in terms of their anatomically distinct compartments, and quantify differences among guts in terms of ratios of body volume to gut volume, relative compartmental volumes, total gut aspect ratios and compartmental aspect ratios. We use multivariate techniques to classify these polychaetes into 4 groups: carnivores with tubular guts; deposit feeders with tubular guts; deposit feeders with 3 gut compartments; and deposit feeders with 4 or 5 gut compartments. Tubular guts, morphological expressions of plug flow, are common among deposit feeders and may allow relatively rapid ingestion rates and short throughput times. Median gut volume per unit of body volume in deposit feeders (31%) is twice that of carnivores (15%) and ranges up to 83% in one deep-sea species. Deep-sea deposit feeders tend to have relatively larger and longer guts than closely-related nearshore and shelf species. Guts of a number of deep-sea deposit feeders and nearshore and shelf deposit feeders from muddy environments are relatively longer and narrower as body size increases, suggesting that digestive diffusion limitations may be important. Gut volume scales as (body volume)1 while ingestion rate scales as (body volume)0.7. If diet and the chemical kinetics of digestion do not change appreciably, throughput time and thus the extent of digestion of given dietary components therefore must increase as a deposit feeder grows. Digestive processing constrainst may be most important in juveniles of species (especially those species with plug-flow guts) that are deposit feeders as adults.