Impresse Corporation

Cristos J Goodrow

Jeffrey B Winner

Phillip C Nelson

Yuri V Smirnov

Yuh-Wen Soung

John L Flight

A scheduling engine and an associated workflow engine may be configured to build workflows that describe sequences of tasks to be performed in a dynamically changing environment. The workflow engine may be configured to monitor the execution of the tasks within the environment and to provide the scheduling engine with information regarding deviations of task executions from the workflows. When such deviations are detected, the workflow engine may trigger the scheduling engine to rebuild the workflows for as yet uncompleted tasks. The scheduling engine may receive the information regarding the deviations via a declarative model of the physical environment. In general, the tasks may be a set of job requests to be processed in a manufacturing environment (e.g., a print shop). Also, the scheduling engine may be made up of an aggregate planner and a detailed scheduler. Aggregate plans for the jobs may be first made for the jobs and then passed to the detailed scheduler for timelining, etc. Building the aggregate plans may be accomplished by selecting a subset of the job requests according to a procedure for packing bins representing the resources of the manufacturing plant.

Method and apparatus for creating adaptive workflows

An order promising scheme includes the ability to query a hierarchical scheduling module configured to generate workflows for a series of jobs to be processed in a manufacturing environment to determine the earliest reasonable completion time for one or more additional jobs to be processed in the manufacturing environment. The querying may involve first querying an aggregate planning level of the hierarchical scheduling module to determine whether the one or more additional jobs may be processed. Further, the querying may require querying a detailed scheduling level of the hierarchical scheduling module to determine whether the one or more additional jobs may be processed in the event that the aggregate planning level returns a negative reply to the first query by the order promising module. The querying of the hierarchical scheduling module may be performed in response to user inquiries submitted via a user interface. The hierarchical scheduling module is kept apprised of a current state of the manufacturing environment through updates to a virtual representation of the manufacturing environment. This may involve updating a model of a print shop environment.

Method and apparatus for order promising

A workflow generated from a declarative model of a real world process represents the procedural steps to accomplish the process. In one embodiment, the declarative model may include a first number of state nodes and a second number of task nodes interconnected with the state nodes. In such cases, generating a workflow may be accomplished by choosing one of a number of paths through the model, each of the paths comprising an alternating series of one or more of the state nodes and one or more of the task nodes with any predecessor state node in one of the paths representing a precondition for a subsequent task node along the one of the paths and any following state node of the subsequent task node along the one of the paths representing a result of applying one or more actions that correspond to that task node. As part of a computer assisted scheduling system, the model may be configured to receive updates reflecting changes in the real-world manufacturing environment. Such changes may represent completed tasks, and/or a change in the availability of one or more resources represented in the model.

Dynamic creation of workflows from deterministic models of real world processes

An aggregate plan for a set of job requests to be processed in a manufacturing environment may be produced given capacities for resources of the manufacturing environment, the capacities being represented by bins in multiple dimensions, some of which may be used by the jobs on an alternative basis. In such a scheme, producing the aggregate plan may be accomplished by selecting a subset of the job requests according to a procedure for packing the bins. For example, packing the bins may be accomplished by selecting from among ordered lists of the job requests grouped according to costs for one or more of the resources. The ordered lists of job requests may be ordered in terms of value. In some cases, at least some of the job requests may have different values versus cost for different ones of the resources. Each alternative be represented as a separate bin. A detailed schedule may be developed from the aggregate plan, the detailed schedule differing from the aggregate plan by including a timeline for the selected jobs.

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San Francisco, CA, United States of America

Cristos J Goodrow