373 results about "Process modeling" patented technology

A software modeling environment is presented that supports the development and execution of software that can be dynamically configured. This is achieved by introducing a design-time object modeling construct called a dynamically configurable type (DCT) that supports the subdivision of an object into a plurality of subsets of semantics and allows dynamic merging of these semantic subsets together in different combinations in order to allow the resultant object to exhibit different semantics over time to serve different purposes. Specific process modeling constructs are included which take advantage of this semantic merging capability. Also included are other supporting design-time and run-time constructs and services. One embodiment of the present invention allows this software modeling environment to be integrated into a standard software development environment, enhancing the modeling capabilities already present.

A Knowledge-Engineering Protocol-Suite is presented that generally includes methods and systems, apparatus for search-space organizational validation, and appurtenances for use therewith. The protocol-suite includes a search-space organizational validation method for synergistically combining knowledge bases of disparate resolution data-sets, such as by actual or simulated integrating of lower resolution expert-experience based model-like templates to higher resolution empirical data-capture dense quantitative search-spaces. Furthermore, from alternative technological vantages, the suite relates to situations where this synergetic combining is beneficially accomplished, such as in control systems, command control systems, command control communications systems, computational apparatus associated with the aforesaid, and to quantitative modeling and measuring tools used therewith. The protocol-suite also includes facile algorithmic tools for use with the method and a process-modeling computer for use in a distributed asynchronous system of process modeling computers.

Methods and systems consistent with the present invention provide an integrated process modeling and project planning tool that allows an enterprise affiliate to improve a workflow that models a process. To improve the workflow, the tool initiates execution of a plan created from the workflow such that an instance of the process is at least partially performed, receives a characteristic about the performance of the plan, and modifies the workflow to reflect the characteristic so that a subsequent plan created from the modified workflow has the received characteristic.

A methodology for process modeling and control and the software system implementation of this methodology, which includes a rigorous, nonlinear process simulation model, the generation of appropriate linear models derived from the rigorous model, and an adaptive, linear model predictive controller (MPC) that utilizes the derived linear models. A state space, multivariable, model predictive controller (MPC) is the preferred choice for the MPC since the nonlinear simulation model is analytically translated into a set of linear state equations and thus simplifies the translation of the linearized simulation equations to the modeling format required by the controller. Various other MPC modeling forms such as transfer functions, impulse response coefficients, and step response coefficients may also be used. The methodology is very general in that any model predictive controller using one of the above modeling forms can be used as the controller. The methodology also includes various modules that improve reliability and performance. For example, there is a data pretreatment module used to pre-process the plant measurements for gross error detection. A data reconciliation and parameter estimation module is then used to correct for instrumentation errors and to adjust model parameters based on current operating conditions. The full-order state space model can be reduced by the order reduction module to obtain fewer states for the controller model. Automated MPC tuning is also provided to improve control performance.

A method for providing closed-loop analysis of a business process includes using modeling objects to extend a modeling language to obtain a representation language. The representation language is used to obtain at least one model of the process. The model is implemented using at least one of simulation, project management analysis, workflow analysis and computer-aided software engineering. The method allows a variety of COTS products to be integrated into a single tool for process modeling and closed-loop analysis of business processes.

Exemplary embodiments include a method for performing business process modeling. The method includes identifying capabilities, activities, and requirements associated with a business problem or an opportunity. The activities are operable for implementing the capabilities and the capabilities are operable for resolving the business problem or exploiting the opportunity. For each of the activities, the method includes selecting at least one corresponding process module that includes listings of attributes applicable to the activities, selecting at least one of the attributes from the listings, and defining transition artifacts for integrating selected process modules. The method also includes compiling the transition artifacts, selected attributes, and selected activities with corresponding process modules, and generating a business process model as a result of the compilation.

A method for synchronizing the control efforts of a plurality of controllers includes determining an apply time for using updated information. The apply time can take into account worst case processing and/or communication delays across a system. Reacting to the updated information only after at the apply time ensures that all system elements are able to react to the updated information in concert. A time stamp indicates when the data was collected. The apply time indicates when the data can be used. Process modeling or simulation is used to estimate system status at the apply time based on the system status at the time of the time stamp, the updated information, and predetermined information regarding the behavior of the system over time. In a document processor, the method allows tightly coupled modules, such as sheet transportation modules, to behave in a cooperative manner when separate modules are in contact with the same sheet.

A process modeling tool for graphically representing a process which includes transactions and events, and for generating computer code representing the process. A graphical tool creates a graphical representation of the transactions and events with graphical symbols, where one or more of such transactions and events may be of an asynchronous nature. A code generator generates computer code in response to information contained in the graphical representation. The computer code is executable on a computer system to cause the computer system to perform one or more operations which emulate the process shown in the graphical representation.

A method is provided for process modeling. The method may include obtaining batch statistics data records associated with one or more input variables and one or more output parameters and selecting one or more input parameters from the one or more input variables. The method may also include generating a computational model indicative of interrelationships between the one or more input parameters and the one or more output parameters based on the data records and determining desired respective statistical distributions of the input parameters of the computational model.

Methods and systems for scenario-based process modeling are described. In one example embodiment, a system for scenario-based process modeling can include a scenario module, a deviations module, a parallel tasks module, and a workflow generation engine. The scenario module is to receive a series of tasks to define a standard process flow. The deviations module is to receive a deviation from the standard process flow. The parallel tasks module is to enable identification of one or more parallel tasks. The workflow generation engine is to generate a workflow model based on the standard process flow, deviation, and one or more parallel tasks.

A method and computer program product for integrating risk management concepts into a standard business process metamodel by defining a set of metamodel extensions to standard process modeling languages that incorporate risk information directly in the process model. The method includes collecting risk-relevant information for addition to a business process model, and enabling visualizing of a risk-extended business process model. using a notation to express notions as failure modes of resources, root cause events, and sources of execution failure and low job output quality directly in the context of process models. Additionally, the method enables the computation of risk-related impacts on the distribution of process performance measures using a Bayesian network model or a discrete-event simulation model.

Automatic generation of processing conditions will be provided, based on a database and process modeling by a computer equipped in semiconductor device fabrication equipment, by using input of wafer processing history including the thickness and quality. The computer equipped in semiconductor device fabrication equipment obtains the wafer processing and inspection results from a production line management computer in order to assist input of the process history. The computer in the fabrication equipment can be connected to computers in a fabrication equipment manufacturer on a communication network to automatically provide process conditions and maintenance schedule.

A system and method for automating a business procedure is disclosed. The workflow management system includes an administrator, a process designer, a workflow database, a process engine and a web client. The system may interact with a form generator and a business application program. The system first analyzes the business process and models the process as a combination of detailed activities. The system assigns the properties to each activity according to the business rules. After modeling the business process and after the business process is initiated, the process engine allocates the workitems to the participant. The system can automate a very complicated business process and can be expanded and adapted to ever-changing business environments.

Modelling a computer based business process having a number of functional steps, involves providing software candidate models (740) of the business process, each specifying the functional steps (750), an arrangement of software application components (770) for carrying out the functional steps, and a design of computing infrastructure (780), for running the software application components, to meet given non functional requirements, and suitable for automated deployment. For each of the candidate models, operation of the business process is simulated (730) according to the respective candidate model and their simulated operation is evaluated against the non-functional requirements. The simulation can help the search for a suitable or optimum deployment to be more efficient and can lead to more efficient usage of shared resources.

A composite technology system RETINA that enables intelligent decision synchronization in real time for continuous, discrete and batch process industries is disclosed. RETINA generates and synchronizes the intelligent decisions that affect the performance and profitability of business operations in real time and helps in analysis that are essential for any successful business operations in any manufacturing industries. RETINA combines the real time integration capability; Predictive analytics capability and adaptive real time process modeling capability to generate intelligent risk-reduced business decisions for continuous, discrete and batch manufacturing processes. RETINA unifies the data from disparate sources or in silos, collates, comprehends and analyses the data, and then convert them into actionable information in real time. Correct decisions are generated, streamlined and shared at the appropriate instant of time with right amount of data to the pertinent personnel to eliminate inefficiencies in operations and performance resulting in tangible profitability.

The invention provides a rapid construction system for zero-coding application software. The rapid construction system comprises the following modules: a data modeling module used for classifying, constructing, managing and synchronizing massive data table types; a form modeling module; a list modeling module; a process modeling module; a capability supporting module providing various bottom layersupport capabilities and interfaces; and a basic function module. The beneficial effects of the invention are that: a development platform which is low in cost, high in efficiency and capable of supporting a building block building form is provided and is used for building various form business systems; and by reducing a development threshold (supporting the use of people with few computer backgrounds or even no computer backgrounds) and improving system development efficiency (wherein codes do not need to be written module by module and can be written through simple dragging), the purpose ofquickly realizing business system development is achieved, quick response to user changes is supported, and configuration is realized.

The invention relates to a multi-phase batch process phase dividing method based on a multiway principal component analysis method, which comprises the following steps: model data acquisition, three dimensional data expansion, two dimension matrix standardization, PCA decomposition, principal component number selection, load matrix decomposition and K-means cluster analysis. The method firstly uses a load matrix of a multiway principal component analytical method model to identify process phase according to timeslice sequence through decomposition deformation, thereby the misunderstanding that the multiway principal component analytical method is not suitable for the multi-phase batch process modeling in the traditional theory is solved. The method not only extracts cross correlation of variable on each timeslice, and simultaneously extracts the self dynamic change characteristic of measure variable in the whole batch at each sampling time for identifying the phase, thereby improving the monitoring efficiency during monitoring process and the accuracy of fault diagnosis result, and providing a new possibility for multi-phase process phase dividing under the condition without process prior knowledge.

The invention provides an SPH (smoothed particle hydrodynamics) algorithm-based simulation method and an SPH (smoothed particle hydrodynamics) algorithm-based simulation system of the process of breaking dam by flood. The simulation method comprises the following steps: A. acquiring on-site geographic spatial information data; B. establishing a dynamical model of the process of breaking dam by flood based on the geographic spatial information data obtained in the step A; C. establishing a geographic entity model according to the geographic spatial information data obtained in the step A; D. analyzing the dynamical model obtained in the step B into an SPH calculation method; E. initializing the geographic entity model obtained in the step C to be hydrodynamics particles and boundary particles for the SPH calculation; F. circularly calculating based on the SPH algorithm; G. carrying out the spatial-temporal process modeling on the calculated value result obtained in the step F to obtain a 3D spatial-temporal model and a database of the process of breaking the dam by flood; and H. dynamically visualizing the 3D spatial-temporal model and the database of the process of breaking dam by flood obtained in the step G. By using the SPH method in the geographic process simulation, the authenticity of the simulation result is effectively improved.

The invention relates to an apparatus for clustering process models each consisting of model elements comprising a text phrase which describes in a natural language a process activity according to a process modeling language grammar and a natural language grammar, wherein said apparatus comprises a process object ontology memory for storing a process object ontology, a distance calculation unit for calculating a distance matrix employing said processing modeling language grammar and said natural language grammar, wherein said distance matrix consists of distances each indicating a dissimilarity of a pair of said process models, and a clustering unit which partitions said process models into a set of clusters based on said calculated distance matrix.

The invention discloses a multidisciplinary collaborative optimization flow modeling and scheduling method and a system based on a business process execution language (BPEL). The method includes the steps of creating multidisciplinary optimization flows based on the BPEL, analyzing flow modeling files, creating multidisciplinary optimization design flow instances, executing the multidisciplinary optimization design flow instances, recording journal files of the multidisciplinary optimization flows in an iterative process, and providing checking service for the journal files. The system comprises a flow creating module, a flow analyzing module, a flow operation instance creation module, a flow instance execution module and a flow execution journal recording module. The method and the system are service-orientated in operation scheduling, support service call among networks, combine with current cloud computing well, can shield modeling principles, modeling forms and input-output inconsistency of different disciplines in modeling, and construct the single-stage and multi-stage multidisciplinary optimization flows rapidly.

Disclosed is a Framework that applies object-oriented state-machine techniques to provide automation, control, and operation of business processes. The Framework provides a working environment from which software applications are created and customized. A visual modeling tool provides an end user with an intuitive and simple way to model processes. Once the model is imported into a database, an Engine automates the process, assigning tasks to users in order to control the accomplishment of each task. The Builder is a customization tool that allows fields or attributes to be customized, defines displays, policies, and business rules, and generates system-initialization data for each application. A Software Development Kit allows the development of applications with specific needs. A Business Model allows distributors to implement applications with the Builder and to obtain earnings both from direct sales of their applications and from royalties for the use and sale of their applications by other distributors.

The present invention relates to a method applying a procedure neural network to establish a procedure predicting model for sparse data. On the basis of the pretreatment of the sparse sample data, a learning algorithm based upon the discrete Walsh transform is applied to increase the learning efficiency and the modeling precision of the procedure neural network. To ensure that the established procedure predicting model can amend the prediction deviations timely, a method of data sampling periodic network rolling learning is adopted based upon the characteristics of the sparse data procedure to conduct an on-line amendment to the network predicting model timely through up-to-date sampled data, thereby improving the accuracy of the predicting model further. The present invention provides an effective approach for solving the modeling problem related to a kind of sparse data procedure.

The invention discloses a just-in-time learning soft measurement modeling method based on a Bayes Gaussian mixture model, and belongs to the field of complex industrial process modeling and soft measurement. The method is used for a time varying industrial process with nonlinearity and non-Gaussianity; through a strategy of updating localities in real time online, a Bayes information criterion isadopted to determine an optimal Gaussian ingredient number; when new test data comes, a posterior probability that the new test data belongs to each Gaussian ingredient is calcuated, a Mahalanobis distance between the new test data and training data is solved, and the posterior probability and the Mahalanobis distance are blended to serve as a similarity index; and finally, one group of data withthe highest similarity is selected from the original training sample to establish a current GPR (Gaussian Process Regression) model, and model output prediction is carried out to achieve an effect onimproving product quality and lowering production cost.