Setup Time Research Articles

A note on scheduling identical parallel machines with preemptions and setup times

We correct, extend and improve recent algorithmic and computational complexity results for the identical parallel machine scheduling problem with preemptions and setup times preceding uninterrupted job parts. The objective is to minimise the makespan. Our results include a proof of strong NP-hardness for an arbitrary number of machines, and a pseudo-polynomial algorithm and an FPTAS for the two machines case.

Optimization of the production planning process in a nuts and dried fruits industry

A resource-constrained machine scheduling problem is addressed in this paper. The problem arises in an industry located in the Canary Islands (Spain) and is characterized by a set of jobs to be completed on multiple processing lines, where each job has a specific processing time and a sequence-dependent setup time. The objective is to maximize the productivity of the processing lines, subject to constraints such as availability of personnel and processing lines, due dates, precedence order, and setup times, among others.In order to solve this problem, an optimization model that represents the problem as a mixed-integer program is proposed. The paper also introduces a constraint satisfaction heuristic to find near-optimal solutions of the problem. The effectiveness of the proposal is demonstrated through computational experiments on a set of real and synthetic instances, showing that the proposed technique is able to find solutions that are close to the optimal ones within a reasonable amount of time.

Kinematic synergies show good consistency when extracted with a low-cost markerless device and a marker-based motion tracking system

Recently, markerless tracking systems, such as RGB-Depth cameras, have spread to overcome some of the limitations of the gold standard marker-based tracking systems. Although these systems are valuable substitutes for human motion analysis, as they guarantee higher flexibility, faster setup time and lower costs, their tracking accuracy is lower with respect to marker-based systems. Many studies quantified the error made by markerless systems in terms of body segment length estimation, articular angles, and biomechanics, concluding that they are appropriate for many clinical applications related to motion analysis. We propose an innovative approach to compare a markerless tracking system (Kinect V2) with a gold standard marker-based system (Vicon), based on motor control assessment. We quantified kinematic synergies from the tracking data of fifteen participants performing multi-directional upper limb movements. Kinematic synergy analysis decomposes the kinematic data into a reduced set of motor primitives that describe how the central nervous system coordinates motion at spatial and temporal level. Synergies were extracted with the recently released mixed-matrix factorization algorithm. Four synergies were extracted from both marker-based and markerless datasets and synergies were grouped in 6 clusters for each dataset. Cosine similarity in each cluster was ⩾0.60 in both systems, showing good consistency of synergies. Good matching was found between synergies extracted from markerless and from marker-based data, with a cosine similarity between matched synergies ⩾0.60 in 5 out 6 synergies. These results showed that the markerless sensor can be feasible for kinematic synergy analysis for gross movements, as it correctly estimates the number of synergies and in most cases also their spatial and temporal organization.

Accelerated evaluation of blocking flowshop scheduling with total flow time criteria using a generalized critical machine-based approach

Despite the considerable advances in the research of the blocking flowshop scheduling problem (BFSP), several unresolved challenges persist. Algorithmic complexity presents hurdles. Although the insertion-based method is considered to generate superior solutions, its high computational demand diminishes the efficiency of algorithms, especially within large-scale sequences. The existing accelerated evaluation methods cannot utilize the existing information to quickly calculate the total flow time or the total tardiness time of the changed sequence after the job insertion, but recalculates it from scratch. This does not significantly reduce computational effort and needs to be further improved.In this paper, we delve into the intrinsic features of these challenges, proposing a generalized accelerated critical machine-based evaluation tailored for the total flow time and tardiness criteria of the BFSP with and without sequence-dependent setup times. First, we propose three theorems, one corollary, and their proofs based on the critical machine. Second, we propose the accelerated evaluation procedure based on these theorems to calculate the objectives related to the total flow time. Third, we also extend the proposed accelerated evaluation method to the BFSP with sequence-dependent setup times, aiming to significantly reduce the time complexity. Finally, we conduct four experiments on five well-known benchmarks (a total of 3540 test instances). Through statistical analysis, it becomes evident that our computational efforts have significantly decreased in computing both the total flow time and the total tardiness time. This performance enhancement is superior to the effectiveness of existing acceleration techniques.

Logic-based Benders decomposition for order acceptance and scheduling on heterogeneous factories with carbon caps

We study an integrated order acceptance and scheduling problem for heterogeneous factories with carbon caps, order-dependent processing speeds, and setup times. Three joint decisions including order selection, order assignment and order sequencing are made to maximize profits, i.e., total revenue minus total production and tardiness cost. Firstly, we develop a mixed integer programming model to simultaneously optimize the three decisions and propose several dominance rules to enhance the model. Secondly, due to the particular structure of the problem, we propose a logic-based Benders decomposition (LBBD) method that decomposes the complicated original problem into a master problem and a number of subproblems. The master problem aims to determine order acceptance and order assignment, and each subproblem is for determining order sequencing in each factory. A branch and bound algorithm is then designed to quickly solve the subproblems. The branch and check framework is implemented to accelerate the solving process of the LBBD. Finally, numerical experiments verify that the proposed dominance rules play a promising role in enhancing the model, and the results of the algorithm comparison experiments show the significant advantages of proposed LBBD algorithm combined with the branch and check framework. Sensitivity experiments reveal that carbon cap serves as a major constraint on order acceptance.

Multi-Device Security Application for Unmanned Surface and Aerial Systems

The use of autonomous and unmanned systems continues to increase, with uses spanning from package delivery to simple automation of tasks and from factory usage to defense industries and agricultural applications. With the proliferation of unmanned systems comes the question of how to secure the command-and-control communication links among such devices and their operators. In this work, we look at the use of the Messaging Layer Security (MLS) protocol, designed to support long-lived continuous sessions and group communication with a high degree of security. We build out MAUI—an MLS API for UxS Integration that provides an interface for the secure exchange of data between a ScanEagle unmanned aerial vehicle (UAV) and an unmanned surface vehicle (USV) in a multi-domain ad-hoc network configuration, and experiment on system limits such as the ciphersuite set-up time and message handling rates. The experiments in this work were conducted in virtual and physical environments between the UAV, USV, and a controller device (all of different platforms). Our results demonstrate the viability of capitalizing on MLS’s capabilities to securely and efficiently transmit data for distributed communication among various unmanned system platforms.

An Assessment of the Role of the Timex Sampling Strategy on the Precision of Shoreline Detection Analysis

Remote video imagery using shoreline edge detection is widely used in coastal monitoring in order to acquire measurements of nearshore and swash features. Some of these systems are constrained by their long setup time, positioning requirements and considerable hardware costs. As such, there is a need for an autonomous low-cost system (~EUR 500), such as Timex cameras, that can be rapidly deployed in the field, while still producing the outcomes required for coastal monitoring. This research presents an assessment of the effect of the sampling strategy (time-lapse intervals) on the precision of shoreline detection for two low-cost cameras located in a remote coastal area in western Ireland, overlooking a dissipative beach–dune system. The analysis shows that RMSD in the detected shoreline is similar to other studies for sampling intervals ranging between 1 s and 30 s (i.e., RMSDmean for Camera 1 = 1.4 m and Camera 2 = 0.9 m), and an increase in the sampling interval from 1 s to 30 s had no significant adverse effect on the precision of shoreline detection. The research shows that depending on the intended use of the detected shorelines, the current standard of 1 s image sampling interval when using Timex cameras can be increased up to 30 s without any significant loss of accuracy. This positively impacts battery life and memory storage, making the systems more autonomous; for example, the battery life increased from ~10 days to ~100 days when the sampling interval was increased from 1 to 5 s.

A 16-Gb/s 3-tap adaptive DFE in 12-nm FinFET CMOS technology

This paper introduces a 3-tap half-rate adaptive decision feedback equalizer (DFE) and a 2-D eye-opening monitor (EOM). A newly developed regenerating sampler (RG-sampler) with smaller setup time and ck2q time is integrated into the proposed DFE, enhancing its performance. To ensure greater robustness, the sign-sign least-mean-squares (SSLMS) algorithm with a pattern filter is employed to adapt DFE tap coefficients. The proposed 2-D EOM accurately captures the shape of the eye diagram using adjustment steps of 1.95ps and 7 mV in the horizontal and vertical directions, respectively. Additionally, by reusing analog components within the adaptive DFE and 2-D EOM modules, significant reductions in silicon area and power consumption are achieved. Implemented in 12-nm FinFET CMOS technology, the transceiver integrated with adaptive DFE and 2-D EOM operates at a data rate of 16 Gb/s over a channel with 30 dB loss at 8 GHz frequency. The proposed adaptive DFE and 2-D EOM occupy a total area of 0.00808 mm2. Measurement results demonstrate that following DFE adaptation, the eye height is 77 mV, and the eye width is 29.25ps at 16 Gb/s.

The Effect of Setup Time in Geotechnical Resistance Factor of Driven Steel Piles in Alberta: a Case Study

Determining the bearing capacity of driven steel piles is a critical concern in geotechnical engineering particularly when constructing major structures in oil and gas and infrastructure projects in Alberta. To verify pile capacity, the pile driving analyzer (PDA) and static load tests (SLTs) are widely used. In recent years, PDA testing has become a regular part of pile quality assurance programs on projects and increasingly used as full-scale load tests. Several studies have shown that geotechnical resistance factor (GRF) values can be calibrated with the aim of PDA testing results which can help designers to potentially reduce the number and length of piles. Nevertheless, uncertainty remains regarding the extent to which the GRF value can be optimized following the implementation of the PDA. In this paper, a database of PDA tests and SLTs are compiled from several projects in Alberta, Canada. The primary objective of this study is to assess the impact of time on the recommended GRFs by several codes. To achieve this, the study employs a well-established probabilistic technique known as Monte Carlo Simulation (MCS) to quantify the influence of time, referred to as “setup time”. To enhance the assessment of setup time’s effect, the recorded bearing capacities are collected during two distinct time points: after the completion of pile installation or the end of drive (EOD) condition, and after a specific setup time at the Beginning-of-Restrike (BOR) condition. The results suggest that by taking into account the time impact, GRF values can be optimized, leading to an increase in factored pile resistance and ultimately resulting in a more cost-effective design process for steel-driven piles.

Crosstalk- and fragmentation-aware survivable routing, modulation, space, and spectrum assignment using Ant Colony Optimization

The use of Space Division Multiplexing (SDM) technology in Elastic Optical Networks (EONs) is a promising solution to improve the transport capability and flexibility required by next-generation applications. In this work, we have illustrated that Ant Colony Optimization (ACO) algorithms can be incorporated into the network control plane and associated with a crankback mechanism to provision and restore lightpaths in a fully distributed manner. In effect, by tackling the challenging Routing, Modulation, Spectrum, and Space Assignment (RMSSA) problem, ACO algorithms can address the inter-core crosstalk and spectrum fragmentation that may limit the potential of the SDM-EON. By comparing different levels of resource state accuracy at the control plane, the simulation results demonstrate the superior performance of the ACO algorithms compared to routing algorithms based on a centralized control plane with a link-state routing protocol, showcasing lower bandwidth blocking rate, comparable restorability, controlled crosstalk levels, and higher scalability, all achieved without a significant increase in setup and restoration times.

Material Characterization Augmented with Artificial Intelligence.

The present paper investigates the application of artificial intelligence to improve the results from simple, non-instrumented, tensile tests, performed with a desktop-size MaCh3D smart universal testing machine. Non-instrumented tensile tests, performed on any testing machine, are affected by both deterministic and random factors that introduce errors in the test results. Specific features of the MaChh3D tester minimize random factors effects on test results while introducing a larger effect of deterministic factors. Artificial intelligence is identified as a novel approach to correct errors in non-instrumented tensile test, capable of simulating a direct strain measure onto the test, replacing traditional contact or non-contact instrumentations (like strain-gages, extensometer and optical measures) that introduce complexity into test procedure and require time for setup. The resulting AI model implementation is described and its performance evaluated in comparison with instrumented tests, also comparing different training strategies. The developed AI-extensometer (artificial intelligence virtual extensometer), is capable of a precise mechanical properties evaluation, with errors from 0 to 10% depending on the specific parameter.

Neighborhood Combination Search for Single-Machine Scheduling with Sequence-Dependent Setup Time

Neighborhood Combination Search for Single-Machine Scheduling with Sequence-Dependent Setup Time

A hybrid genetic programming algorithm for the distributed assembly scheduling problems with transportation and sequence-dependent setup times

This paper investigates a distributed assembly permutation flow-shop scheduling problem with transportation and sequence-dependent set-up times (DAPFSP-TSDST). A hybrid genetic programming (HGP) algorithm is proposed to optimize the makespan of the assembly stage, which inherits the merits of genetic programming (GP) and neighbourhood search operators. In HGP, a hybrid problem-specific initialization heuristic is developed to make populations more diverse. Multiple neighbourhood search operators are employed as the leaf nodes, which are vital for the success of GP. A product shift strategy is proposed to strengthen its exploitability. In addition, a simulated annealing criterion is adopted to make the HGP explore more thoroughly. Finally, statistical and computational experiments are carried out on the benchmark instances. The results exhaustively identify the notable competitiveness of the HGP algorithm in coping with the DAPFSP-TSDST.

Evaluation of an online SSVEP-BCI with fast system setup

The brain–computer interface (BCI) plays an important role in neural restoration. Current BCI systems generally require complex experimental preparation to perform well, but this time-consuming process may hinder their use in clinical applications. To explore the feasibility of simplifying the BCI system setup, a wearable BCI system based on the steady-state visual evoked potential (SSVEP) was developed and evaluated. Fifteen healthy participants were recruited to test the fast-setup system using dry and wet electrodes in a real-life scenario. In this study, the average system setup time for the dry electrode was 38.40 seconds and that for the wet electrode was 103.40 seconds, which are times appreciably shorter than those in previous BCI experiments, enabling a rapid setup of the BCI system. Although the electroencephalogram (EEG) signal quality was low in this fast-setup BCI experiment, the BCI system achieved an information transfer rate of 138.89 bits/min with an eight-channel wet electrode and an information transfer rate of 70.59 bits/min with an eight-channel dry electrode, showing that the overall performance was close to that in traditional experiments. In addition, the results suggest that the solutions of a multi-channel dry electrode or few-channel wet electrode may be suitable for the fast-setup SSEVP-BCI. This fast-setup SSVEP-BCI has the advantages of simple preparation and stable performance and is thus conducive to promoting the use of the BCI in clinical practice.

An inexpensive moist chamber culture technique for finding microbiota on live tree bark.

Traditional moist chamber cultures (MCs) prepared in aseptic laboratory environments using sterile Petri dishes are commonly used to quantify the microbiota of rough-bark tree species and woody vines. MCs are typically expensive and may be difficult to make, so a less expensive option made from easily available supplies was developed. These cost-friendly MCs were compared with standard laboratory methods to demonstrate their efficacy. Modified MCs were made using inexpensive, store-bought supplies; compared to a standard laboratory setting, the modified MCs are shown to be less expensive with a faster setup time and larger size that facilitates a variety of tree and woody vine species. MC use resulted in the discovery of new species of fungi and myxomycetes with associated locality records. We provide detailed instructions for creating modified MCs, as well as a list of myxomycete species and their associated bark characteristics, pH values, and water-holding capacity. This new, low-cost MC technique makes the study of microbiota more inclusive and accessible for those in research laboratories, classrooms, and homes, including both amateurs and professionals. MCs are easy to prepare, versatile, and applicable for many areas of botany and the biological sciences, potentially allowing exploration into unexplored areas in urban ecosystems.

Coblation versus BiZact extra-capsular tonsillectomy in adults: a randomized control trial.

Tonsillectomy is a frequently performed otolaryngological procedure and is associated with significant postoperative pain and bleeding. A number of studies have investigated methods to reduce pain and bleeding. Coblation and BiZact devices have both been claimed to have favourable pain outcomes following tonsillectomy. This study was designed to investigate these two techniques in a direct comparison of postoperative pain and bleeding. In this single blinded, randomized control trial, 61 patients were randomly assigned to undergo tonsillectomy with either the BiZact or Coblation device. Pain scores were collected for 14 days postoperatively using a Visual Analogue Score scale. Secondary outcome data was collected for duration of surgery, intra-operative bleeding, return to normal, and secondary bleeding rates. Coblation was found to have lower postoperative pain on day 1 (P < 0.05). BiZact was found to have lower postoperative pain on day 7 (P < 0.05) and day 11 (P < 0.05). Pain scores for other days were not significant. There was no significant difference in set-up time, procedural time and return to normal activities. The BiZact group had a longer time to achieve haemostasis (P < 0.001) and greater intraoperative blood loss (P < 0.01). There was a trend towards more significant secondary bleeding in the BiZact arm, however, this study was not adequately powered to assess this finding. Both Coblation and BiZact devices appear to provide a safe and effective method for tonsillectomy in adults. Reduced pain on day 1 may make Coblation more suitable for day-case surgery.

Iterated variable neighborhood search for integrated scheduling of additive manufacturing and multi-trip vehicle routing problem

This study addresses a novel problem structure for integrated scheduling of additive manufacturing and delivery processes. In the manufacturing process, we consider batch production of parts, simulating Selective Laser Melting technology in parallel additive manufacturing machines with heterogeneous specifications. A batch production, referred to as a build, must consist of parts with homogenous material. During the production run, sequence-dependent material setup times occur in between builds. In the delivery process, parts are delivered in batches using a limited number of homogenous capacitated vehicles. Each vehicle might perform multi-trips. Thus, the route for each trip and departure schedule among trips must be decided. In this regard, batch delivery is independent to batch production. The problem objective function is to minimize the total completion time of all parts. For optimally solving the problem, a mixed-integer linear programming model is devised. To solve larger problems sizes under a lower computation time, an iterated variable neighborhood search algorithm with embedded rule-based heuristics is proposed. The computational experiment denotes that the proposed algorithm with route minimization rule effectively solves small-scale problems, while capacity usage maximization rule performs the best in large-scale problems and outperforms other existing metaheuristics. Further result analysis is also performed to provide managerial insights.

A cooperative grey wolf optimizer for the joint flowshop scheduling problem with sequence-dependent set-up time

With the complexity involved in manufacturing products, many companies use multiple processes to complete product processing. Most studies have been concerned with single production but have neglected the widespread joint flowshop scheduling problem (JFSP). In this article, a cooperative grey wolf optimizer (CGWO) is developed to solve the JFSP. First, according to the features of the JFSP, a corresponding mathematical model is constructed, and three collaborative strategies and random generation are proposed to initialize the population. In the process of searching for prey, a discretized search for prey update mechanism is proposed, which is conducive to balancing exploration and exploitation. An energy-saving strategy is proposed to decrease energy consumption. Moreover, four local search mechanisms are developed for different optimization objectives to enhance the performance of the method in attacking the prey. The results show that the CGWO is effective in solving the JFSP.

G-code evaluation in CNC milling to predict energy consumption through Machine Learning

Computerized Numeric Control (CNC) plays an essential role in highly autonomous manufacturing systems for interlinked process chains for machine tools. NC-programs are mostly written in standardized G-code. Evaluating CNC-controlled manufacturing processes before their real application is advantageous due to resource efficiency. One dimension is the estimation of the energy demand of a part manufactured by an NC-program, e.g. to discover optimization potentials. In this context, this paper presents a Machine Learning (ML) approach to assess G-code for CNC-milling processes from the perspective of the energy demand of basic G-commands. We propose Latin Hypercube Sampling as an efficient method of Design of Experiments to train the ML model with minimum experimental effort to avoid costly setup and implementation time of the model training and deployment.

Volatile versus propofol sedation after cardiac valve surgery: a single-center prospective randomized controlled trial

BackgroundOptimal intensive care of patients undergoing valve surgery is a complex balancing act between sedation for monitoring and timely postoperative awakening. It remains unclear, if these requirements can be fulfilled by volatile sedations in intensive care medicine in an efficient manner. Therefore, this study aimed to assess the time to extubation and secondary the workload required.MethodsWe conducted a prospective randomized single-center trial at a tertiary university hospital to evaluate the postoperative management of open valve surgery patients. The study was randomized with regard to the use of volatile sedation compared to propofol sedation. Sedation was discontinued 60 min after admission for critical postoperative monitoring.ResultsWe observed a significantly earlier extubation (91 ± 39 min vs. 167 ± 77 min; p < 0.001), eye-opening (86 ± 28 min vs. 151 ± 71 min; p < 0.001) and command compliance (93 ± 38 min vs. 164 ± 75 min; p < 0.001) using volatile sedation, which in turn was associated with a significantly increased workload of a median of 9:56 min (± 4:16 min) set-up time. We did not observe any differences in complications. Cardiopulmonary bypass time did not differ between the groups 101 (IQR 81; 113) versus 112 (IQR 79; 136) minutes p = 0.36.ConclusionsUsing volatile sedation is associated with few minutes additional workload in assembling and enables a significantly accelerated evaluation of vulnerable patient groups. Volatile sedation has considerable advantages and emerges as a safe sedation technique in our vulnerable study population.Trial registration: Clinical trials registration (NCT04958668) was completed on 1 July 2021.