Scheduling Tool Research Articles

A Schedule Optimization Tool for Destructive and Non-Destructive Vehicle Tests

Whenever an auto manufacturer refreshes an existing car or truck model or builds a new one, the model will undergo hundreds if not thousands of tests before the factory line and tooling is finished and vehicle production beings. These tests are generally carried out on expensive, custom-made vehicles because the new factory lines for the model do not exist yet. The work presented in this paper describes how an existing intelligent scheduling software framework was modified to include domain-specific heuristics used in the vehicle test planning process. The result of this work is a prototype scheduling tool that optimizes the overall given test schedule in order to complete the work in a given time window while minimizing the total number of vehicles required for the test schedule. Initial results are presented that show a reduction in required test vehicles compared to manual scheduling of the same tasks as well as increased capability to ask “what-if” questions to further improve the schedule.

SU-E-T-103: Development and Implementation of Web Based Quality Control Software

Purpose: Historically many radiation medicine programs have maintained their Quality Control (QC) test results in paper records or Microsoft Excel worksheets. Both these approaches represent significant logistical challenges, and are not predisposed to data review and approval. It has been our group's aim to develop and implement web based software designed not just to record and store QC data in a centralized database, but to provide scheduling and data review tools to help manage a radiation therapy clinics Equipment Quality control program. Methods: The software was written in the Python programming language using the Django web framework. In order to promote collaboration and validation from other centres the code was made open source and is freely available to the public via an online source code repository. The code was written to provide a common user interface for data entry, formalize the review and approval process, and offer automated data trending and process control analysis of test results. Results: As of February 2014, our installation of QAtrack+ has 180 tests defined in its database and has collected ∼22 000 test results, all of which have been reviewed and approved by a physicist via QATrack+'s review tools. These results include records for quality control of Elekta accelerators, CT simulators, our brachytherapy programme, TomoTherapy and Cyberknife units. Currently at least 5 other centres are known to be running QAtrack+ clinically, forming the start of an international user community. Conclusion: QAtrack+ has proven to be an effective tool for collecting radiation therapy QC data, allowing for rapid review and trending of data for a wide variety of treatment units. As free and open source software, all source code, documentation and a bug tracker are available to the public at https://bitbucket.org/tohccmedphys/qatrackplus/.

THE IRRIGATION SCHEDULING IGDROID TOOL

THE IRRIGATION SCHEDULING IGDROID TOOL DIOGO FRANSCISCO BORBA RODRIGUES¹ E CERES DUARTE GUEDES CABRAL DE ALMEIDA² 1 Doutorando, Programa de Pos-Graduacao em Engenharia Agricola, Universidade Federal Rural de Pernambuco, diogo.borbar@gmail.com 2 Engenheira Agronoma, Profa Doutora, Colegio Agricola Dom Agostinho Ikas, Universidade Federal Rural de Pernambuco, ceres@codai.ufrpe.br 1 ABSTRACT The speed of information processing of data collected in fields can be a deciding factor in the efficiency of an irrigation system, responding appropriately to crops' water requirements. The objective of this paper was to describe a new tool for irrigation scheduling, called IGdroid. This tool is a mobile phone application for use by farmers who use irrigation and have some climate monitoring equipment, such as rain gauges and evaporation pans, providing irrigation advice in areas based on inputs and outputs data without internet connection. The development process and the main functions of the application are described in this paper. The software is inserted in the farmer's mobile phone to schedule everyday irrigation. Soil properties, irrigation system and crop data must be inserted in the database, so the farmer can insert climatological data in her/his mobile phone on a daily basis. The application can record multiple irrigated areas with different crops, soil types and irrigation systems, and reports irrigation requirements daily. If the farmer needs to irrigate, the app informs her/him of the water depth (mm) and how long to run the system (in hours) in each area. This app also allows simulation of irrigation scenarios in agricultural planning. Keywords: irrigated agriculture, Android, App Inventor

Performance of simple irrigation scheduling calendars based on average weather data for annual ryegrass

Poor irrigation management in pastures can lead to yield and quality reduction as well as loss of income through extra pumping and leaching of nitrate fertiliser. A number of irrigation scheduling techniques of varying levels of sophistication have been developed over the years to address limited irrigation water availability and maximise productivity. Despite this, the adoption of irrigation scheduling tools by farmers remains low. The objective of this study was to assess the use of simple irrigation scheduling calendars based on average weather data to improve irrigation management in ryegrass. The calibrated Soil Water Balance (SWB) model was used to generate simple irrigation calendars and assess effectiveness for different scenarios by mechanistically simulating water dynamics and pasture growth. Scheduling irrigation using the calendars gave similar irrigation applications, water losses and yields compared to a more scientific real-time scheduling (in response to soil water depletion by the crop). While site-specific irrigation scheduling calendars can easily be generated by consultants and irrigators, even simpler monthly estimates of average daily water use can also be useful. Application of calendars by farmers is encouraged to improve water and nutrient use efficiency of irrigated pastures, if real-time irrigation scheduling is not employed.

A generalized network flow model for the multi-mode resource-constrained project scheduling problem with discounted cash flows

An effective project schedule is essential for enterprises to increase their efficiency of project execution, to maximize profit, and to minimize wastage of resources. Heuristic algorithms have been developed to efficiently solve the complicated multi-mode resource-constrained project scheduling problem with discounted cash flows (MRCPSPDCF) that characterize real problems. However, the solutions obtained in past studies have been approximate and are difficult to evaluate in terms of optimality. In this study, a generalized network flow model, embedded in a time–precedence network, is proposed to formulate the MRCPSPDCF with the payment at activity completion times. Mathematically, the model is formulated as an integer network flow problem with side constraints, which can be efficiently solved for optimality, using existing mathematical programming software. To evaluate the model performance, numerical tests are performed. The test results indicate that the model could be a useful planning tool for project scheduling in the real world.

Effective Project Scheduling Under Workspace Congestion and Workflow Disturbance Factors

Effective project management implies the use of advanced planning and scheduling methods that allow to determine feasible sequences of activities and to complete a project on time and on budget. Traditional scheduling tools like fundamental Critical Path Method (CPM) and various methods for Resource Constrained Project Scheduling Problem (RCPSP) and Time Constrained Project Scheduling Problem (TCPSP) have many shortcomings for construction projects where spatial factor plays a critically important role. Previous attempts to interpret space as a specific resource were successful for particular problems of line-of-balance scheduling, space scheduling, dynamic layout planning, horizontal and vertical logic scheduling, workspace congestion mitigating, scheduling multiple projects with movable resources, spatial scheduling of repeated and grouped activities and motion planning. However, none of these methods considers the spatio-temporal requirements in a holistic framework of generic RCPSP problem and provides feasible results accounting for workspace and workflow factors. In this paper we start with the classical RCPSP statement and then present mathematically strong formalisation of the extended generalised problem, taking into account workspace congestion and workflow disturbance constraints specified in practically meaningful and computationally constructive ways. For the generalised RCPSP problem an effective scheduling method is proposed. The method tends to minimise the project makespan while satisfying timing constraints and precedence relations, not exceeding resource utilisation limits, avoiding workspace congestions and keeping workflows continuous. The method reuses so-called serial scheduling scheme and provides for additional computational routines and heuristic priority rules to generate feasible schedules satisfying all the imposed requirements. Advantages of the method and prospects for its application to industrial needs are outlined in the paper too.

Increasing the Accuracy of a Prefab Building Design Process Simulation Using Simulated Annealing

Monte-Carlo simulation analysis has been discussed in project management literature as tool for proactive scheduling and to gain better insights into projects which are characterized by a high level of complexity and uncertainty, such as the design phase of prefab building projects. The application of simulation as proactive scheduling tool in construction projects is hampered by limited accessibility of proper input data, though, because of long project duration, the often temporary organization and multidisciplinary nature of such projects. In this study we use simulated annealing to adjust parameters of a simulation model for which the simulation outcome is sensitive to data perturbation by making use of data from related parameters which is easier to estimate. The applicability of the approach was demonstrated on a real life project, the construction of a 1100 m2 residential building in Sweden. More precisely, we used Design Structure Matrix simulation, i.e. an activity network based Monte-Carlo simulation technique with which stochastic project evolution (deviations from the planned activity sequence due to unexpected iteration of sub-processes) can be simulated, to model the workflow of the design process of the observed project. Then, by means of the simulated annealing approach, we adjusted the rework probabilities (model parameter) such that the frequencies of executed activities in simulated activity sequences fitted the frequencies as observed in the real project. Adjusting input data by using prior knowledge of the dependencies of the project activities and cross analysis with related data that is easy to estimate would help to increase the accuracy of simulations when access to statistical data of the input variable in question is limited. The suggested approach is interesting for practitioners who work with standardized design processes (e.g. as part of standardized building systems) and continuous improvement.

Deadlock Avoidance and Detection in Railway Simulation Systems

Avoiding or preventing deadlocks in simulation tools for train scheduling remains a critical issue, especially when combined with the objective of minimization (e.g., the travel times of the trains). The deadlock avoidance and detection problem is revisited, and a new deadlock avoidance algorithm, called DEADAALG, is proposed based on a resource reservation mechanism. The DEADAALG algorithm is proved to be exact; that is, it either detects an unavoidable deadlock resulting from the input data or provides train scheduling free of deadlocks with the scheduling algorithm SIMTRAS. Moreover, it is shown that SIMTRAS is a polynomial time algorithm with an O(|S|&Middot;|T|2 log |T|) time complexity, where T is the set of trains and S is the set of sections in the railway topo logy. Numerical experiments are conducted on Canada's Vancouver–Calgary single-track corridor of Canadian Pacific Railway Limited. Then it is shown that SIMTRAS is efficient and provides schedules of a quality that is comparable with that of an exact optimization algorithm in tens of seconds for up to 30 trains/day over a planning period of 60 days.

Real Time Control of Water Distribution Systems Using a Multi-criteria Decision-support Tool for Optimal Water Network Management – A Case Study

This paper addresses network management at resource zone level through the use of a real-time, multi-criteria pump scheduling tool, Miser PS. Miser PS was integrated within Anglian Water operations as a stand-alone, semi-automated, open-loop system. It is estimated that the application of Miser PS has achieved a 3.4% energy reduction on the studied system equivalent to £217000 or 428tn of CO 2eq per year and improved asset knowledge and asset management. In addition, Miser PS has facilitated scenario testing to prepare for planned and unplanned events such as drought events and improved network resilience.

406 小規模産業用・業務用需要家を対象とした設備稼働スケジューリングツールにおける実務的課題(省エネルギー・エネルギー貯蔵)

The authors developed a scheduling tool for electric demand management of small scale industrial customers after the Great East Japan Earthquake. Through a survey of practical requirements for the tool, several issues have been revealed, for example, consideration of process line of factories and that of power demand profile of each facility. In this paper, we reported about the issues and discussed about the approach for them.

Комплексный метод составления расписаний для сложных индустриальных программ с учетом пространственно-временных ограничений

Effective project management implies the use of advanced planning and scheduling methods that allow to determine the feasible sequences of activities and to complete a project on time and on budget. Traditional scheduling tools like fundamental Critical Path Method (CPM) and various methods for Resource Constrained Project Scheduling Problem (RCPSP) and Time Constrained Project Scheduling Problem (TCPSP) have many shortcomings for the construction projects where spatial factor plays critically important role. Previously taken attempts to interpret space as a specific resource were successful for particular problems of line-of-balance scheduling, space scheduling, dynamic layout planning, horizontal and vertical logic scheduling, workspace congestion mitigating, scheduling multiple projects with movable resources, spatial scheduling of repeated and grouped activities, motion planning. However, none of these methods considers the spatio-temporal requirements in a holistic framework of generic RCPSP problem and provides feasible results accounting for workspace and workflow factors. In the paper we start with the classical RCPSP statement and then present mathematically strong formalization of the extended generalized problem taking into account workspace congestion and workflow disturbance constraints specified in practically meaningful and computationally constructive ways. For the generalized RCPSP problem an effective scheduling method is proposed. The method tends to minimize the project makespan while satisfying timing constraints and precedence relations, not exceeding resource utilization limits, avoiding workspace congestion and keeping workflows continuous. The method reuses so-called serial scheduling scheme and provides for additional computational routines and heuristic priority rules to generate feasible schedules satisfying all the imposed requirements. In order to evaluate the method, benchmark sets are proposed and investigated. Advantages of the method and prospects for its application to industrial needs are outlined in the paper too.

Applying Lean Construction to Construction Project

Lean construction is aimed to improve construction performance by eliminating wastes that do not add value to the customer. This project studies lean construction and its application in concrete construction projects at both the operation and project levels. In conjunction with a concrete contractor, actual concrete construction projects were observed, and problem areas contributing to delay and other wastes were identified. At the project level, the lack of coordination among subcontractors was cited as one of the major factors contributing to schedule delays. This paper proposes to use the last planner concept, the linear scheduling method, and the graphic schedule method to improve communication and look-ahead scheduling. Related software was developed for implementing this scheduling tool. At the operation level, a systematic approach of was identification, operation re-design, and employee training was applied to reduce wastes found in the field operation. A case study of bulkhead installation was used to demonstrate this approach, and a 3D animation was created for employee training.

CloudMoni: A Monitoring Framework for on Demand Virtual Machine Allocation in Cloud Data Centers

Cloud computing is a new computational and commercial model. It brings the illusion of a virtually infinite computing infrastructure/platform that provides advanced features. The increased number of VMs and applications in virtualized data centers triggers serious scalability concerns with regards to monitoring. Many features of Cloud need supports from underlying Cloud monitoring system. There is a lack of a lightweight monitoring tool for on-demand virtual machine scheduling in open literature, especially considering traffic analysis, elastic capacity provisioning, and power consumption. In this paper, a monitoring framework for Infrastructure as a Service (IaaS), CloudMoni, is proposed. CloudMoni can report utilization and status, also provides sufficient information for developers and users to have deep insights on on-demand virtual machine management and scheduling, which involving traffic analysis, elastic capacity provisioning, power metering of virtual machines. The prototype application of proposed architecture is presented in the end.

A hybrid method based on wavelet, ANN and ARIMA model for short-term load forecasting

In the new competitive electricity markets, the necessity of appropriate load forecasting tools for accurate scheduling is completely evident. The model which is utilised for the forecasting purposes determines how much the forecasted results would be dependable. In this regard, this paper proposes a new hybrid forecasting method based on the wavelet transform, autoregressive integrated moving average (ARIMA) and artificial neural network (ANN) for short-term load forecasting. In the proposed model, the autocorrelation function and the partial autocorrelation function are utilised to see the stationary or non-stationary behaviour of the load time series. Then, by the use of Akaike information criterion, the appropriate order of the ARIMA model is found. Now, the ARIMA model would capture the linear component of the load time series and the residuals would contain only the nonlinear components. The nonlinear part would be decomposed by the discrete wavelet transform into its sub-frequencies. Several ANNs are applied to the details and approximation components of the residuals signal to predict the future load sample. Finally, the outputs of the ARIMA and ANNs are summed. The empirical results show that the proposed hybrid method can improve the load forecasting accuracy suitably.

Optimization of shipyard space allocation and scheduling using a heuristic algorithm

In this article we describe the development of a tool that allows planners to efficiently and effectively plan space within valuable areas of a shipyard. Traditionally, space is considered as resource; however, it is difficult to accurately account for and plan its consumption with the currently available planning software’s. The spatial scheduling tool described in this article can be used by planners to manually or automatically reserve space within the shipyard for construction of large blocks over the entire erection period of the ship. The software is coupled with a heuristic optimization solver inspired by an algorithm used for "3D bin-packing problems." The result is the ability to efficiently generate and compare multiple space allocation alternatives in a reduced time with the ultimate goal of maintaining the critical ship erection schedule. A better solution than manual or semi-automatic allocation of blocks can be obtained through the optimization module.

Irrigation and Rootstock Influence on Water Use, Tree Growth, Yield, and Fruit Quality at Harvest at Different Ages of Trees in ‘Pacific Gala’ Apple

During various ages of tree between 2002 and 2007, the effects of four rootstocks and two irrigation systems using a crop evapotranspiration-based (ETc) water scheduling on water use, tree growth, yield, and fruit quality at harvest in ‘Pacific Gala’ apple [(Malus ×domestica) Borkh] were studied. The use of ETc when a precise crop coefficient value (Kc), modified by percentage of ground shade (GS) and tree canopy maturity (M) was used, provided a reliable tool for irrigation scheduling of ‘Pacific Gala’ apple. Young trees with a full sprinkler (FS) system received an average of 872.3 mm (5616.8 L/tree), whereas those with full drip (FD) received 448.9 mm (2921.1 L/tree). However, when trees were mature, trees with a FS system received an average of 994 mm (6461.7 L/tree), whereas trees with a FD received 614.1 mm (3996 L/tree) of irrigation water per growing season. Trees on ‘Budagovsky 9’ (‘B.9’) had smaller trunk cross-sectional area (TCA) and higher yield efficiency, whereas those on ‘Supporter4’ (‘Sup.4’) had larger TCA and lower yield efficiency than those on other rootstocks in all years of the study. Trees on ‘Nic.9’ (‘RN29’) always had higher yield per tree as compared with those on other rootstocks. Trees on ‘RN29’ often had higher but trees on ‘B.9’ had lower fruit weight than did those on other rootstocks. Trees on ‘Sup.4’, despite their lower yields, had smaller fruits than those on ‘RN29’ every year and thus were not suitable for planting. Fruit from trees on ‘B.9’ and ‘Cornell-Geneva30’ (‘G.30’) often had higher soluble solids concentration (SSC) and starch degradation pattern (SDP) than those other rootstocks. Fruits from trees on ‘G.30’ also had lower firmness and higher stem-end cracking, suggesting that this rootstock advances maturity in ‘Pacific Gala’ apple. Trees with FS irrigation had higher TCA than those with the FD system. Trees with the FD system were more precocious and had higher yield per tree, yield efficiency, and fruit weight than trees with the FS system when they were young. However, these differences were not significant when trees matured. ‘Pacific Gala’ fruit from trees with FS consistently had better color than those with the FD system every year. Fruits from young trees with the FD system often had higher SDP and lower firmness than those from FS irrigation.

ENGINEERING A SAP FLOW SENSOR FOR IRRIGATORS

ENGINEERING A SAP FLOW SENSOR FOR IRRIGATORS

Summer deficit irrigation in a hedgerow olive orchard cv. Arbequina: relationship between soil and tree water status, and growth and yield components

Stem water potential (Phi-stem) is a useful tool for irrigation scheduling in tree crops, provided threshold values for growth and production are determined for each physiological period. Four irrigation treatments were evaluated in a hedgerow olive orchard. Control (CON) was irrigated using soil water sensors to maintain the root zone close to field capacity. Severe water deficits were applied by irrigating at 30% CON from end of fruit drop to end of July (DI-J) or from end of July until beginning of oil synthesis (DI-A). Less severe water deficit was applied in July and August by irrigating at 50% CON (DI-JA). Continuous measures of soil moisture, Phi-stem and shoot length were recorded in all treatments. Fruit dry weight and oil content were measured at the end of the experimental period and at harvest. Relative extractable soil water to 0.8 m depth (REW) and Phi-stem were highly correlated and influenced by irrigation treatment. Shoot growth, fruit characteristics and oil production were correlated to Phi-stem. Shoot growth was reduced by 50% relative to CON by irrigating at Phi-stem of -1.3 MPa. Fruit dry matter and oil content (g fruit-1) were linearly reduced as mean summer Phi-stem decreased. Oil production was highly related with Phi-stem in August but not in July. Water can be saved in July by irrigating at Phi-stem of -2.9 MPa but Phi-stem should be maintained higher than -2.0 MPa in August to prevent decrease of oil production.

Cost‐effective importance measure

PurposeThe purpose of this paper is to propose a new measure for criticality analysis of different components of a production plant, called cost‐effective importance measure (CEIM) that considers the component's performance, system structure and economic aspects.Design/methodology/approachIn this work, an explorative literature study covering the concept of importance measure and criticality analysis has been carried out on contemporary literature. The literature study shows that the commonly used importance measures consider the probability of failure of a component and systems structure, and ignore the effect or severity of failures, which is an important factor in engineering decision making. It is not clear how to use the concept of importance measure in combination with cost parameter. Hence, a cost‐effective importance measure (CEIM) is defined and a case study is presented, to demonstrate the application of the proposed importance measure.FindingsThe paper indicates that CEIM useful for the analysis of production plants where reliability and cost of break down are of paramount importance.Research limitations/implicationsThe concept of CEIM is demonstrated using only a case study of a belt conveyor system in the underground mine of Singareni Coal Company Ltd. However, the concept of CEIM can be used in other area.Practical implicationsThe concept of CEIM can be a handy and effective tool for scheduling of inspection, maintenance and fault diagnosis and these activities can be carried out as per the rank of the components to maximize the benefits in skilled manpower crunch. It also indicates that the upgradation of the production plant's performance can also be done by improving performance of components with relatively large CEIM values.Originality/valueIn this paper, the concept of importance measure is extended to include the effect of severity of failures and cost parameter in the criticality analysis.

Scheduling for machinery fleets in biomass multiple-field operations

In the light of the current development toward large, and consequently, complicated agricultural production systems, such as systems of biomass production as bioenergy resource, the demand for advanced management tools, such as fleet management tools for scheduling and coordination of multiple vehicles working in multiple-fields, will be increased. In this paper, a planning approach for scheduling sequential tasks involved in biomass harvesting and handling operations performed by machinery teams was presented. The approach determines in which fields each machine has to operate, in what sequence, in which period of time, and the total operational cost of the resulting optimised schedule, taking into account specific factors such as the location and area of fields, available agricultural equipment, and the task times estimation based on the specific machine performance. The cost was included as an additional feature of the individual schedules providing the decision maker the ability to assess the relationship and trade-off between cost and time for each potential derived machinery combination within the available machinery fleet.