Timing optimization of multiphase sequential logic

Redundancy addition and removal (RAR) uses automatic test pattern generation (ATPG) techniques to identify logic optimization transforms. It has been applied successfully to combinational and sequential logic optimization and to layout driven logic synthesis for FPGAs. We present an improved RAR technique that allows to one to identify new types of optimization transforms and it is more efficient because it reduces the number of ATPG runs required. Also, we apply the RAR method to timing optimization. The experimental results show that this improved RAR technique produces significant timing optimization with very little area cost.

We present a new technique for defining, analysing, and simplifying digital functions, through hand-calculations, easily demonstrable therefore in the classrooms. It can be extended to represent discrete systems beyond the Boolean logic. The method is graphical in nature and provides complete ‘‘implementation-free” description of the logical functions, similar to binary decision diagrams (BDDs) and Karnaugh-maps (K-maps). Transforming a function into the proposed representations (also the inverse) is a very intuitive process, easy enough that a person can hand-calculate these transformations. The algorithmic nature allows for its computing-based implementations. Because the proposed technique effectively transforms a function into a scatter plot, it is possible to represent multiple functions simultaneously. Usability of the method, therefore, is constrained neither by the number of inputs of the function nor by its outputs in theory. This, being a new paradigm, offers a lot of scope for further research. Here, we put forward a few of the strategies invented so far for using the proposed representation for simplifying the logic functions. Finally, we present extensions of the method: one that extends its applicability to multivalued discrete systems beyond Boolean functions and the other that represents the variants in terms of the coordinate system in use.

Collaborative robotics is increasingly considered in manufacturing to improve efficiency while reducing operators physical and cognitive workloads. However, the lack of comprehensive methodologies has limited the consistent implementation of human–robot collaborative workstations across industries. Existing approaches are often fragmented, require robotics expertise, and pose challenges for non-experts, leading to suboptimal station designs and inefficient task allocation. This study presents a structured design framework to transition traditional assembly processes into collaborative ones. The framework provides a practical, scalable solution for optimizing collaborative workstations, balancing performance, ergonomics, and industrial applicability. It starts from the analysis of the assembly tasks, followed by classification and allocation between human operators and robots, and concludes with virtual prototyping and performance optimization through simulation using a commercial tool. The adopted methodology integrates task analysis, ergonomic assessment, and workspace design to ensure accessible and efficient implementation. Validated through two industrial case studies involving a gear pump and a worm gearbox, the approach demonstrated significant reductions in cycle time and notable improvements in the ergonomic working conditions. Additionally, physical prototyping and testing conducted within a research collaborative cell further confirmed the achieved results. • A design framework for designing human–robot collaborative assembly workstations is proposed. • The method integrates digital tools for task analysis, ergonomic assessment and workspace design. • A virtual prototype of the cell is used to assess assembly performance and ergonomic conditions. • Two industrial case studies validate the approach in real production contexts.

Technology can improve cycle time and overcome distance when developing products for an international market. Some of the technological solutions include electronic communications networks, desktop publishing equipment, and computer-assisted translation software. By implementing these solutions, Texas Instruments has reduced cycle time in translating technical product documentation for the European market. >

In automotive production cells, complex processes involving multiple robots must be optimized for cycle time. We investigated using symbolic GR(1) controller synthesis for automating multi-robot task planning. Given a specification of the order of tasks and states to avoid, often multiple valid strategies can be computed; in many states there are multiple choices to satisfy the specification, such as choosing different robots to perform a certain task. To determine the best choices under the consideration of movement times and probabilities that robots may be interrupted for repairs or corrections, we combine the execution of the synthesized controller with Monte Carlo Tree Search (MCTS), a heuristic AI-planning technique. The result is a model-at-run-time approach that we present by the example of a multi-robot spot welding cell. We report on experiments showing that the approach (1) can reduce cycle times by choosing time-efficient movement sequences and (2) can choose executions that react efficiently to interruptions by choosing to delay tasks that, if an interruption of one robot should occur later, can be reallocated to another robot. Most interestingly, we found, however, that (3) in some cases there is a conflict between time-efficient movement sequences and ones that may react efficiently to probable future interruptions—and when interruption probabilities are low, increasing the time allocated for MCTS, i.e., increasing the number of sample simulations made by MCTS, does not improve cycle time.

<div class="htmlview paragraph">The Engine Supplier Base Initiative (ESBI) is a joint Air Force/Industry cooperative agreement aimed at achieving affordable precision investment cast airfoil and large structural components for man-rated gas turbine engines. The ESBI program will obtain these goals through the implementation of business and technology improvements with specific focus on increased product quality and reduced cycle time. This program has brought together competitors in the business to solve sector wide problems. This paper presents the framework of the teaming approach as well as results achieved in quality and cycle time improvements through technical and business process improvements.</div>

A number of grid-generation and CFD-process software tools have been developed which greatly improve the ability to perform overset CFD analysis of complex con gurations. These tools have been applied to the task of generating grids and computing the ow eld about two di erent high-lift aircraft con gured for landing: a Boeing 777-200, and a High-Wing Transport with externally blown aps. The high-lift owelds of both aircraft were simulated using the OVERFLOW solver. A Navier-Stokes simulation of a complete Boeing 777-200 aircraft con gured for landing was obtained in less than 50 labor days with a lift coe cient which di ers from experimental data by only 1.2%. This is an order of magnitude reduction in the cycle time for the entire computational process compared to a similar high-lift simulation e ort that took place two years earlier. The new software was utilized to perform a oweld analysis of a ap-rigging modi cation for the Boeing 777-200 aircraft in only four days. The software was also utilized to simplify Aerospace Engineer. yChief, Aerospace Operations Modeling O ce. Senior Member AIAA. zResearch Engineer. xPrincipal Engineer. Senior Member AIAA. {Engineer/Scientist Specialist. Member AIAA. kPrincipal Engineer. Copyright c 2000 by the American Institute of Aeronautics and Astronautics, Inc. No copyright is asserted in the United States under Title 17, U.S. Code. The U.S. Government has a royalty-free license to exercise all rights under the copyright claimed herein for Governmental Purposes. All other rights are reserved by the copyright owner. grid generation of the High-Wing Transport for many di erent geometric con gurations. The reductions in computational cycle time are primarily the result of the use of an automatic script system that streamlines the overset grid preparation process. Analysis of the process shows that over-setting the the grid system is now the most labor-intensive part of a single-point analysis; however, for multi-point analyses, multiple viscous ow-solver runs are costly.

Today many manufacturing firms are focusing on cycle or throughput time reduction to gain a competitive advantage. In many instances, cycle times at individual workstations are adversely affected by unscheduled machine breakdowns. In this paper, existing closed-form approximations for the expected cycle time at a parallel machine workstation with general process and interarrival times and for the variability in departures from the workstation are used to demonstrate how the mean and variance of machine repair or downtime affects cycle times at a given workstation and downstream workstations. Results from the machine interference literature are used to characterize the dependence of repair time on a base stock inventory policy used for the replenishment of spare components. Expressions for the mean and approximations for the variance of repair times are obtained for machines with either a single critical component or a series of critical components when such components fail exponentially. Numerical examples are given to illustrate the effect that spare component inventory levels have on the average station cycle time and departure variability. A methodology for base stock parameter selection that considers the trade-off between reduced cycle times and inventory investment is also presented.

Today’s construction business relies on first-to-market product strategies to gain competitive advantages and increase profit margins. This has created an increased demand for a high performance capital project delivery system that can achieve a dramatic reduction in project cycle time. Very few decision tools and guidelines exist to assist owners in choosing appropriate delivery systems and project strategies to radically reduce the project cycle time from the preplanning stage through start up. The research presented in this paper surveyed the construction owners and architectural/engineering/construction firms to identify projects that have achieved greater than 25% reduction in overall project cycle time when compared to current industry standards. The data collected were analyzed to determine the techniques that facilitate radical reduction in project cycle time. These techniques include, best practices and schedule reduction techniques as well as the various management techniques employed on the projects identified by the Construction Industry Institute (CII). This research also identified the barriers to radical schedule reduction. The research concludes that radical schedule reduction well in excess of 25% can be achieved through the selective employment of management techniques, schedule reduction techniques and CII best practices. Almost every construction manager can utilize this research to improve project performance whether for radical reduction or simply more effective execution.

This article presents two area/latency optimized gate level asynchronous full adder designs which correspond to early output logic. The proposed full adders are constructed using the delay-insensitive dual-rail code and adhere to the four-phase return-to-zero handshaking. For an asynchronous ripple carry adder (RCA) constructed using the proposed early output full adders, the relative-timing assumption becomes necessary and the inherent advantages of the relative-timed RCA are: (1) computation with valid inputs, i.e., forward latency is data-dependent, and (2) computation with spacer inputs involves a bare minimum constant reverse latency of just one full adder delay, thus resulting in the optimal cycle time. With respect to different 32-bit RCA implementations, and in comparison with the optimized strong-indication, weak-indication, and early output full adder designs, one of the proposed early output full adders achieves respective reductions in latency by 67.8, 12.3 and 6.1 %, while the other proposed early output full adder achieves corresponding reductions in area by 32.6, 24.6 and 6.9 %, with practically no power penalty. Further, the proposed early output full adders based asynchronous RCAs enable minimum reductions in cycle time by 83.4, 15, and 8.8 % when considering carry-propagation over the entire RCA width of 32-bits, and maximum reductions in cycle time by 97.5, 27.4, and 22.4 % for the consideration of a typical carry chain length of 4 full adder stages, when compared to the least of the cycle time estimates of various strong-indication, weak-indication, and early output asynchronous RCAs of similar size. All the asynchronous full adders and RCAs were realized using standard cells in a semi-custom design fashion based on a 32/28 nm CMOS process technology.

Stability analysis and optimization algorithms for the set-up of infeed centerless grinding

As a part of the company's digitalization project, the Well Delivery Process (WDP) software solution was successfully developed and launched in early 2021. By using this solution, engineers benefit from the project objectives like process standardization, well design quality, and well planning cycle time reduction. The WDP software consists of a series of integrated well delivery workflows including well design, drilling execution monitoring, and closeout reports within a single cloud-based platform. The system also provides users with many automation features such as well design rules validation, offset well analysis, risk analysis, automated calculations, and digital reports (drilling programs). Through this paper, we share our experiences and observations on the system development and implementation, and also challenges and limitations that we faced to roll it out successfully. In our conventional practices before the digital transformation, drilling engineers had their individual practices/formats to perform the well delivery process using various applications and techniques. Computer applications were used to generate and compile a drilling program, but there was no standard way of performing this process. In situations where the design parameters and/or subsurface information change, engineers should have repeated the entire process to revise the design and/or the drilling program manually. To standardize the process, minimize repetitive tasks, and provide engineers with all required digital tools, the first solution (a prototype computer program) was developed in-house to prove the concept. After multiple peer reviews and trials, we used the prototype program to specify user requirements for generating the WDP software solution. An agile methodology was utilized to engage all drilling engineers in each sprint of the WDP development phase to ensure that their requirements are fulfilled. Upon completion of the development phase, a comprehensive User Acceptance Test (UAT) was conducted followed by training sessions before the cut-off date for switching from the manual process to the WDP digital workflow. Switching from existing practice to a new way of work is always challenging especially when it comes to introducing new software. There was some resistance at the start-up period due to users' unfamiliarity with the software and also software bugs that were not found during testing periods and UAT. A support team was set up to ensure immediate action on users' requirements and any technical issues with the software. During the challenging transition period, all users were fully supported until make sure they are enough familiar with the system to complete the task effectively. The support team deployed hotfixes (bug fixing) as quickly as possible with no major impact on the drilling programs' timeline, monitored the system performance on daily basis, and gathered feedback for further improvements. At present, the WDP is the primary system used by all drilling engineers in the company's domestic assets as an integrated end-to-end well delivery workflow that provides an improved design quality in a shorter planning time. More than 200 well design workflows have been initiated and approved through the system since it is being used. Based on the recent users' satisfaction survey and feedback, an overall rating of 4.2 from 5 shows the WDP solution's effectiveness with many popular and useful features especially offset well analyzer and well design dashboards. As one of the first end-to-end workflow generations in the drilling engineering process, the WDP could save the working time up to 35-40% (voted by users) through a centralized dataset platform and its holistic approach to process standardization/automation. Besides design quality and cycle time improvement, the system also enables advanced data analytics for further automation and enhancements.

In the last two decades, computational enhancements highly contributed to the increase in popularity of DTI algorithms. This cause the successful use of Decision Tree Induction (DTI) using recursive partitioning algorithms in many diverse areas such as radar signal classification, character recognition, remote sensing, medical diagnosis, expert systems, and speech recognition, to name only a few. But recursive partitioning and DTI are two faces of

Inefficient clinic systems leading to prolonged wait times at primary care clinics are a source of frustration for patients, physicians, staff and administration. Measuring and shortening cycle time has the potential to improve patient experience, staff satisfaction and patient access by moving more patients through in a shorter cycle time. Limited studies have demonstrated that improvements can be made to cycle time and may result in improved patient satisfaction. Most of these studies have focused their efforts on improving efficiency at the front end of the cycle. Our aim was to improve cycle time for the whole visit to less than 60 min within 1 year by engaging our team in brainstorming solutions, presenting regular measurements to our team for review and holding regular meetings to plan rapid improvement cycles. Over the course of 1 year (2017), we were able to reduce cycle time by 12% from 71 to 65 min and to improve patient satisfaction with care. Despite the reduction in cycle time, we maintained high satisfaction scores from patients who felt that the doctor spent enough time with them. We learnt the value of engaging our team, frequent measurement for reporting, adequate staffing at the beginning of clinic, and the value of MA staff acting in a flow coordinator role. We have not only maintained this improvement but also made further small gains over the subsequent 2 years, and by April 2019, our cycle time is at 60 min, despite a marked increase in patient volume. Additional work on the time after the patient is roomed and waiting for a doctor, and further analysis of the physician workflow would be important next steps to drive further improvement.

The scale and complexity of search space are important factors deciding the solving difficulty of an optimization problem. The information of solution space may lead searching to optimal solutions. Based on this, an algorithm for combinatorial optimization is proposed. This algorithm makes use of the good solutions found by intelligent algorithms, contracts the search space and partitions it into one or several optimal regions by backbones of combinatorial optimization solutions. And optimization of small-scale problems is carried out in optimal regions. Statistical analysis is not necessary before or through the solving process in this algorithm, and solution information is used to estimate the landscape of search space, which enhances the speed of solving and solution quality. The algorithm breaks a new path for solving combinatorial optimization problems, and the results of experiments also testify its efficiency.