Timing Analysis Techniques Research Articles

Data-Driven Identification and Analysis of Waiting Times in Business Processes

AbstractReducing waiting times in end-to-end business processes is a recurrent concern in the field of business process management. The uptake of data-driven approaches in this field in the past two decades, most notably process mining, has created new opportunities for fine-grained analysis of waiting times based on execution data. As a result, a wide range of approaches for waiting time identification and analysis on the basis of business process execution data have been reported in the literature. In many instances, different approaches have considered different notions of waiting time and different causes for waiting time. At present, there is a lack of a consolidated overview of these manifold approaches, and how they relate to or complement each other. The article presents a literature review that starts with the question of what approaches for identification and analysis of waiting time are available in the literature, and then refines this question by adding questions which shed light onto different causes and notions of waiting time. The survey leads to a multidimensional taxonomy of data-driven waiting time analysis techniques, in terms of purpose, causes, and measures. The survey identifies gaps in the field, chiefly a scarcity of integrated multi-causal approaches to analyze waiting times in business processes, and a lack of empirically validated approaches in the field.

Productivity Improvement of Assembly Line-by-Line Balancing Technique: Case Study Textile Manufacturing Company Karachi Pakistan

The study on assembly line balancing theory and concept, focusing on the textile sector in Karachi, Pakistan, specifically the stitching department of a company, aimed to enhance efficiency through meticulous analysis and optimization. By employing time and motion analysis techniques, the research sought to identify and eliminate redundant activities, ensuring a seamless workflow with minimal idle time. The methodology employed involved a comprehensive observation of the entire production process, starting from stitching through to packing. This involved using a stopwatch to meticulously analyze each step of the process, thus gaining insight into the current operational dynamics of the assembly line. Line balancing was ensured by calculating Standard Allowed Minutes (SAM), assessing capacity, and determining the required manpower and machine resources. To further refine the efficiency of the stitching line, data collection was conducted using stopwatch techniques, to devise an improved layout. By reducing processing time and minimizing unproductive intervals, the study aimed to establish a foundation for enhanced productivity and streamlined work orders. Various tools were utilized to scrutinize the procedures involved in the production process, encompassing activities, operator proficiency, equipment efficiency, and material usage. This comprehensive approach aimed to optimize the workflow, making it more ergonomic and conducive to efficient operations while ensuring worker satisfaction. The study's analysis specifically targeted the stitching operations related to sheet sets, with a focus on minimizing the number of machines and achieving optimal line capacity. Significant reductions in machine requirements were achieved, with the number of machines for both sheet sets and fitted sheets being reduced substantially. Capacity calculations based on SAM and machine numbers demonstrated the achievement of production targets. Moreover, manpower requirements were reassessed and optimized, resulting in a reduction in the number of workers required for packing operations, thereby further enhancing efficiency.

Novel Spectral Approaches in Mathematical Bioacoustics Based on Real Time Analysis and Modern Computational Mathematical Techniques Using Digital Signal Processing and Analog Signal Processing Hardware (Review Lecture)

This review publication is an expanded version of the 2015 lecture at the III Moscow Seminar on Mathematical Bioacoustics and Analog Signal Processing in Physiology. Unlike the original 2015 version, this version includes developments by E.D. Adamovich and F.K. Orekhov, as well as a number of graphic materials of historical value. The work proposes new principles or approaches for multifactori/multimodal analysis of various bioacoustic signals based on N-dimension complex spectral analysis of different (bio) physical variables - “bioacoustic fingerprinting” and “bioacoustic footprinting”. Hadware-based technical examples of possible uses of this approache are given for the breef annotation in the text of this lecture.

Search for quasi-periodic oscillations in TESS light curves of bright Fermi Blazars

ABSTRACT In a previous paper, we reported evidence for quasi-periodicities in the Transiting Exoplanet Survey Satellite (TESS) light curves of BL Lacerate and two other blazars found serendipitously in the Sloan Digital Sky Survey (SDSS) active galactic nuclei catalogue. In this work, we find tentative evidence for quasi-periodic features in the TESS observations of five sources in the fourth catalogue of the Fermi–Large Area Telescope sources: J090453.4−573503, J2345−1555, B0422+004, J002159.2−514028, and B0537−441. We analysed the TESS light curves of these blazars that we extracted using a customized approach. The quasi-periodic oscillations (QPOs) are searched for using two timing analysis techniques: generalized Lomb–Scargle periodogram and weighted wavelet Z-transform. Their apparent periods lie in the range of 2.8–6.5 d and have at least 3σ significance in both of these methods. QPOs at such time-scales can originate from the kink instability model which relates the quasi-periodic feature with the growth of kinks in the magnetized relativistic jets. We performed Markov Chain Monte Carlo simulations to obtain the posterior distribution of parameters associated with this model and found the kink period consistent with previous studies.

Event-Based Two-Step Transmission Mechanism for the Stabilization of Networked T-S Fuzzy Systems With Random Uncertainties.

This article studies an event-based two-step transmission mechanism (TSTM) in the control design for networked T-S fuzzy systems. The transmission task is achieved in two steps. Consecutive triggering packets are relabeled in the first step by applying a traditional event-triggered mechanism (ETM). Then a probabilistic approach is employed to determine which packet is a real release packet (RRP) in the second step. This event-based TSTM is particularly suitable for scenarios in which traditional ETMs are unable to determine which packets are redundant. By discarding most of the unnecessary data packets, especially when the system is tending toward stability, the burden on the network bandwidth is reduced. To establish a control strategy for T-S fuzzy-based nonlinear systems with random uncertainties, a new timing analysis technique is proposed. Additionally, the necessary conditions for a nonlinear system's mean-square asymptotic stability (MSAS) are derived. Finally, two practical applications demonstrate the effectiveness of the suggested transmission mechanism in networked T-S fuzzy systems.

Switching Activity Factor-Based ECSM Characterization (SAFE): A Novel Technique for Aging-Aware Static Timing Analysis

Switching Activity Factor-Based ECSM Characterization (SAFE): A Novel Technique for Aging-Aware Static Timing Analysis

Diagnosis of localized defects in floating bush bearings through time-frequency domain analysis

Bearings play a crucial role in the functionality of rotating machinery, and any defects in these components can result in machine failure. Detecting, diagnosing, and prognosing bearing faults are crucial steps in machine failure diagnostics to prevent malfunctions and breakdowns. While various methods exist for fault detection, including acoustic emission analysis, visual inspection, thermography, ultrasonic, motor current analysis, wear-debris analysis, oil analysis, and vibration analysis, the latter stands out as a popular non-destructive method. This paper focuses on time and frequency domain vibration analysis techniques for detecting faults in floating bush bearings. Particularly beneficial for online monitoring, remote and non-human intervention areas, and hazardous locations, the time-frequency domain approach enhances diagnostic capabilities. The vibration data collected during these experiments has been rigorously analyzed using data acquisition system and applied a comprehensive approach that includes evaluating the data in both the time and frequency domains, as well as utilizing advanced signal processing techniques, notably the high-frequency resonance technique. Test results underscore the effectiveness of specific parameters in identifying defects: waveform, form factor, parameter K, and cepstrum excel in pinpointing external defects, while kurtosis, crest factor, and skewness prove adept at identifying internal faults. In the frequency domain, the enveloped spectrum emerges as a robust method for comprehensive defect detection. The vibration data presented in this paper will prove to be an invaluable resource for professionals engaged in the field of vibration measurement and analysis.

ANALYSIS OF THE EFFECT OF DOWN TIME ON PRODUCTIVITY AT PT. EASTERN PEARL FLOUR MILLS MAKASSAR

Productivity is a comparison between the results achieved (output) with the overall required resources (input) or a comparison between the results achieved with the role of labor per unit time.
 The purpose of this study was to study Down Time analysis techniques for productivity in a wheat processing company (PT. Eastern Pearl Flour Mills Makassar), which produces wheat flour products of the Gatotkaca, Gunung, Kompas and Gerbang types. Down Time is the amount of time when a tool/machine cannot operate due to failure, but the factory can still operate because there are still other tools/machines that can replace functions so that the production process can still run.
 Based on the data analysis of the calculation of down time for manpower, it shows that the existence of down time during the process will affect the level of productivity (actual and standard). The value of down time from the calculation of working hours minus work effectiveness results in down time for each production area each month. The manpower down time results from all areas, namely in the area of 0 minutes/month. While the amount of data from the analysis of down time calculations for machines in all areas has a higher number of machine down times, namely in the milling area of 28 hours. And for the lowest results, namely in the area of unloading, cleaning, and packing, it is 0 hours.

Adaptive Clock Management of HLS-generated Circuits on FPGAs

In this article, we present Syncopation , a performance-boosting fine-grained timing analysis and adaptive clock management technique for High-Level Synthesis-generated circuits implemented on Field-Programmable Gate Arrays. The key idea is to use the HLS scheduling information along with the placement and routing results to determine the worst-case timing path for individual clock cycles. By adjusting the clock period on a cycle-by-cycle basis, we can increase performance of an HLS-generated circuit. Our experiments show that Syncopation improves performance by 3.2% (geomean) across all benchmarks (up to 47%). In addition, by employing targeted synthesis techniques along with Syncopation, we can achieve 10.3% performance improvement (geomean) across all benchmarks (up to 50%). Syncopation instrumentation is implemented entirely in soft logic without requiring alterations to the HLS-synthesis toolchain or changes to the FPGA, and has been validated on real hardware.

EDF scheduling for distributed systems built upon the IEEE 802.1AS clock - A theoretical-practical comparison

Existing response time analysis and optimization techniques for real-time distributed systems show that EDF schedulers feature better scheduling capabilities when a global clock reference can be used; this form of scheduling is known as global-clock EDF. In this context, precise clock synchronization is an enabling technology for future distributed real-time systems that want to leverage EDF scheduling. The IEEE 802.1AS protocol can be considered a stable technology for this purpose, as it is part of the Time-Sensitive Networking (TSN) family of standards to provide real-time communication over Ethernet. This paper presents a system architecture for applying global-clock EDF scheduling in distributed systems with soft real-time requirements. It also presents experiments to (1) assess the synchronization capabilities of the clock synchronization mechanism in the proposed architecture, (2) evaluate the performance of different scheduling deadline assignment techniques, and (3) contrast the theoretical results obtained by the schedulability analysis against those obtained through the execution of these experiments.

Influence of Meteorological Processes on cGPS Measurements of Crustal Movements

Surface displacement measurements collected using continuous Global Positioning System (cGPS) stations include the contribution of both endogenic processes (e.g., plate tectonics, isostasy) and exogenic processes that show seasonal variation (e.g., climate). These seasonal variations distort the tectonic signals and limit the usefulness of short-term investigations. This paper explores cGPS and meteorological time series collected in southern Africa and investigates whether the usefulness of cGPS time series can be improved by accounting for the seasonal effects of the dominant meteorological processes. The study is carried out using time, frequency, and time-frequency domain signal processing (inferential) analysis techniques. It was found that from the considered atmospheric processes, thermally-induced effects, which are not corrected for in the cGPS data, are the most prominent meteorological contributors in the vertical annual deformation component observed in cGPS time series. The effects of heave action (due to seasonal subsurface water infiltration and absorption, as well as changes in the water table) and changes of water mass distribution (caused by infiltration, transportation, extractions, and evaporation) on the displacement time series are much smaller. This suggests that correcting for thermal expansion, contraction, and thermal-induced errors could reduce the annual seasonal deformation component observed in cGPS position measurements in southern Africa and, most probably, in other parts of the world subjected to large seasonal variations in atmospheric temperatures. Reducing the magnitude of the seasonal components would increase the usefulness of short-term cGPS campaigns.

Early timing analysis based on scenario requirements and platform models

Distributed, software-intensive systems (e.g., in the automotive sector) must fulfill communication requirements under hard real-time constraints. The requirements have to be documented and validated carefully using a systematic requirements engineering (RE) approach, for example, by applying scenario-based requirements notations. The resources of the execution platforms and their properties (e.g., CPU frequency or bus throughput) induce effects on the timing behavior, which may lead to violations of the real-time requirements. Nowadays, the platform properties and their induced timing effects are verified against the real-time requirements by means of timing analysis techniques mostly implemented in commercial-off-the-shelf tools. However, such timing analyses are conducted in late development phases since they rely on artifacts produced during these phases (e.g., the platform-specific code). In order to enable early timing analyses already during RE, we extend a scenario-based requirements notation with allocation means to platform models and define operational semantics for the purpose of simulation-based, platform-aware timing analyses. We illustrate and evaluate the approach with an automotive software-intensive system.

Low-power Near-data Instruction Execution Leveraging Opcode-based Timing Analysis

Traditional processor architectures utilize an external DRAM for data storage, while they also operate under worst-case timing constraints. Such designs are heavily constrained by the delay costs of the data transfer between the core pipeline and the DRAM, and they are incapable of exploiting the timing variations of their pipeline stages. In this work, we focus on a near-data processing methodology combined with a novel timing analysis technique that enables the adaptive frequency scaling of the core clock and boosts the performance of low-power designs. We propose a near-data processing and better-than-worst-case co-design methodology to efficiently move the instruction execution to the DRAM side and, at the same time, to allow the pipeline to operate at higher clock frequencies compared to the worst-case approach. To this end, we develop a timing analysis technique, which evaluates the timing requirements of individual instructions and we dynamically scale the clock frequency, according to the instructions types that currently occupy the pipeline. We evaluate the proposed methodology on six different RISC-V post-layout implementations using an HMC DRAM to enable the processing-in-memory (PIM) process. Results indicate an average speedup factor of 1.96× with a 1.6× reduction in energy consumption compared to a standard RISC-V PIM baseline implementation.

Anion intercalation pseudo-capacitance performance of oxygen-deficient double perovskite prepared via facile wet chemical route

Oxygen-deficient perovskite oxides manifest capability of multi-functional application with remarkable physical and chemical properties. In the present study, Sr2FeCoO6-δ, an oxygen-deficient perovskite has been effectively prepared through easy wet chemical method followed by thermal processing at 1000 °C temperature. The Rietveld refinement of Sr2FeCoO6-δ, X-ray diffraction pattern indicates the structure of the cubic phase of Sr2FeCoO6-δ with Pm3‾m symmetry. The super-capacitive behavior of Sr2FeCoO6-δ electrode; investigated first time and electrochemical analysis technique performed using potassium hydroxide electrolyte solution show magnificent outcomes, i.e., the specific capacitance 263 F/g at 1 A/g. Further, electrode stability has been tested by performing 3000 charging-discharging cycles and 57% retention was attained, which indicates the electrode capability for energy storage application.

Characteristics of Jupiter's X‐Ray Auroral Hot Spot Emissions Using Chandra

AbstractTo help understand and determine the driver of jovian auroral X‐rays, we present the first statistical study to focus on the morphology and dynamics of the jovian northern hot spot (NHS) using Chandra data. The catalog we explore dates from December 18, 2000 up to and including September 8, 2019. Using a numerical criterion, we characterize the typical and extreme behavior of the concentrated NHS emissions across the catalog. The mean power of the NHS is found to be 1.91 GW with a maximum brightness of 2.02 Rayleighs (R), representing by far the brightest parts of the jovian X‐ray spectrum. We report a statistically significant region of emissions at the NHS center which is always present, the averaged hot spot nucleus (AHSNuc), with mean power of 0.57 GW and inferred average brightness of 1.2 R. We use a flux equivalence mapping model to link this distinct region of X‐ray output to a likely source location and find that the majority of mappable NHS photons emanate from the pre‐dusk to pre‐midnight sector, coincident with the dusk flank boundary. A smaller cluster maps to the noon magnetopause boundary, dominated by the AHSNuc, suggesting that there may be multiple drivers of X‐ray emissions. On application of timing analysis techniques (Rayleigh, Monte Carlo, Jackknife), we identify several instances of statistically significant quasi‐periodic oscillations (QPOs) in the NHS photons ranging from 2.3 to 36.4 min, suggesting possible links with ultra‐low frequency activity on the magnetopause boundary (e.g., dayside reconnection, Kelvin‐Helmholtz instabilities).

Accurate Estimation of Power Consumption for Binary Comparator System using Back Tracking

This paper presents a design of a binary comparator circuit using minimum fan-in logic gates (NAND-NOR) for achieving low power-delay-product (PDP). A 2-bit binary comparator circuit is re-designed to minimize fan-in of logic gates. Utilizing the concept of 2–bit comparator, a general gate-level architecture of a comparator system is proposed for higher input operands. A back-tracking model has been proposed in this work to estimate the worst-case performance in terms of delay and power or PDP for binary comparator circuits. It combines the advantages of the simulation-based method for power estimation and dynamic timing analysis (DTA) techniques for timing analysis. This work has also been extended for 20, 16, 14, 10, and 7-nm FINFET technology. The comparator circuits are simulated on Pyxis schematic tool by Mentor Graphics.

Myths and realities of endurance time analysis: Discussion/Comments Regarding “Seismic assessment of deep water bridges in reservoir considering hydrodynamic effects using endurance time analysis” by Yutao Pang, Li Cai, Wei He, and Li Wu; Ocean Engineering, 2020, 198:106846

This discussion is based on the paper by Pang et al. (2020) (hereafter identified as “the original authors” and “the original paper” or “the reference paper”). The original authors employed the endurance time analysis (ETA) and incremental dynamic analysis (IDA) techniques to investigate the probabilistic response of a deep water bridge in a reservoir. They derived multiple fragility curves using both techniques. Derivation of ETA-based fragility functions in the original paper is not fully consistent with the nature of seismic fragility curves. The underpinning concept of fragility curves is tied with ground motion record-to-record (RTR) variability, while the conventional ETA does not offer such an ability. We discussed several underlying assumptions in the ETA method, as well as different sources of ground motion RTR variability (from IDA technique) which may affect the logarithmic dispersion in a fragility curve (and it is unseen in conventional ETA method).

Efficient IR Drop Analysis and Alleviation Methodologies Using Dual Threshold Voltages with Gate Resizing Techniques

IR drop impacts circuit delay time and reliability. The IR drop comes from unexpected peak current (Ipeak) consumption. This paper proposes an efficient methodology with an in-house EDA tool named IPR to analyze and reduce the Ipeak. IPR adopts dual threshold voltages (Vth) and gate resizing technique; it also lowers the short, dynamic, and static leakage current consumption without degrading the system performance. IPR consists of two parts: Ipeak analysis and Ipeak alleviation processes. Nonlinear static/dynamic timing analysis techniques, in cooperation with dual Vth cell library, provides two kinds of accurate Ipeak calculation methods used in IPR. Using the incremental timing analysis, the Ipeak processing time can be accelerated. Demonstration of the ISCAS89 benchmark circuits shows that IPR can reduce Ipeak by 39%, power consumption by 14%, and delay time by 19%. In addition, it provides 334 times faster computation with 2% and 10% estimation errors of the Ipeak and power in gate-level, respectively, as compared to circuit level simulation results.

Generalized and Scalable Offset-Based Response Time Analysis of Fixed Priority Systems

Abstract Offset-based response time analysis techniques obtain tight worst-case response time (WCRT) bounds by accounting release time dependencies between tasks. The maximum response time variation of a task or a message (i.e., the difference between the worst-case and best-case response time) is used to compute the end-to-end delays of distributed systems (Palencia and Harbour, 1998), (Tindell and Clark, 1994). Hence, the WCRT evaluation plays an important role in determining tight end-to-end delays of distributed systems. In real-time theory, there exist two approaches to compute the WCRT of a task: the classical response time analysis (RTA) approach and the modular performance analysis with the Real-Time Calculus (MPA-RTC). MPA-RTC has its roots in Network Calculus (NC). MPA-RTC offers more powerful abstraction than RTA based techniques and allows composition in terms of tasks, event streams, and resource sharing which makes it a strong candidate to analyze distributed systems (Wandeler, 2006), (Perathoner, 2011). However, one of the key limitations of the MPA-RTC is its inability to handle offset dependencies between tasks, whereas the classical RTA techniques can handle them. In this paper, we propose a method to consider offset dependencies between tasks using an MPA-RTC framework for a fixed priority scheduler in a uniprocessor system. Hence, our approach leverages the advantages of the expressive MPA-RTC framework model. We propose novel heuristics and approximation to reduce the inherent complexity of an offset-based RTA. We quantitatively evaluate the effectiveness of our approach to the state-of-the-art classical offset-based RTA techniques.

HRM: Merging Hardware Event Monitors for Improved Timing Analysis of Complex MPSoCs

The performance monitoring unit (PMU) in multiprocessor system-on-chips (MPSoCs) is at the heart of the latest measurement-based timing analysis techniques in critical embedded systems. In particular, hardware event monitors (HEMs) in the PMU are used as building blocks in the process of budgeting and verifying software timing by tracking and controlling access counts to shared resources. While the number of HEMs in current MPSoCs reaches hundreds, they are read via performance monitoring counters whose number is usually limited to 4-8, thus requiring multiple runs of each experiment in order to collect all desired HEMs. Despite the effort of engineers in controlling the execution conditions of each experiment, the complexity of current MPSoCs makes it arguably impossible to completely remove the noise affecting each run. As a result, HEMs read in different runs are subject to different variability, and hence, those HEMs captured in different runs cannot be “blindly” merged. In this work, we focus on the NXP T2080 platform where we observed up to 59% variability across different runs of the same experiment for some relevant HEMs (e.g., processor cycles). We develop a HEM reading and merging (HRM) approach to join reliably HEMs across different runs as a fundamental element of any measurement-based timing budgeting and verification technique. Our method builds on order statistics and the selection of an anchor HEM read in all runs to derive the most plausible combination of HEM readings that keep the distribution of each HEM and their relationship with the anchor HEM intact.