International Business Machines Corporation

Brian Trevor Denton

Robert J Milne

Kenneth Jeffrey Fordyce

Alfred Degbotse

Richard Gerard Burda

Robert A Orzell

Chi-Tai Wang

Sanjay R Hegde

Sameer T Shikalgar

John Joseph Forrest

Jacqueline N Ward

Guogang Zuo

Steven H Voldman

Cuc Kim Huynh

Thomas Robert Ervolina

Rahul Nahar

Andrew James Sullivan

Shreesh S Tandel

Stuart H Smith

Satyadeep Vajjala

Grant Lindsey MacKay

Chih-Hui Chang

Samik Raychaudhuri

Mark Gregory Pleszkoch

Vivek Sharma

Elizabeth L Williamson

J Kenneth Coppola

Brent Scott Elmer

A scheduling optimizer system, method and program product that analyzes a device for sensitivities, such as ESD sensitivities, and allows for modification of a floor schedule of the assembly unit of the device based on the sensitivity of the device while improving the overall performance of the assembly unit are disclosed. The scheduling optimizer analyzes sensitivity data for a device during operation of the assembly unit on the floor schedule. The floor schedule is then optimized based on the analyzed sensitivity data.

Optimized scheduling based on sensitivity data

The invention disclosed here is a method for achieving simultaneous consideration of multiple customer demand dates within an advanced planning system. The invention provides a method of production planning that considers multiple due dates. The invention solves a production planning model based upon the second (commit) date to produce a first solution, sorts the demand records in order of importance, and then re-solves the production planning model based upon the first (request) date to produce a second solution. The re-solving process is performed on each demand item in the sorted order of importance. The invention optimizes between the first solution and the second solution. Before re-solving the production planning model, the invention changes the lower bound constraints on backorder variables. The re-solving process changes the required date for a single demand item, and this re-solving process is repeated for all demand items that have a first (request) date that is before a corresponding required date. The invention reports the optimal solution produced during the optimizing process. The system and method integrate the consideration of multiple demand dates with an advanced planning system for optimizing established planning objectives (e.g. customer service, short lead times, low inventory, and prioritized allocation of supply and capacity) to compute a feasible production plan for the division.

Method for simultaneously considering customer commit dates and customer request dates

Approximating cycle times within a material flow network is disclosed. One embodiment includes assigning an approximate cycle time for completion of a part number PN within the material flow network by using a model that rounds the approximate cycle time to a nearest aggregate time period and adjusting the assigned approximate cycle time based on a mathematical function representing an aggregate accuracy of an aggregation of cycle times throughout the material flow network.

Approximating cycle times within material flow network

A method and computer program product for scheduling product lots through operations of a manufacturing line. The method including: selecting a set of sequential operations required to manufacture the lots; partitioning the product lots into designated lots and non-designated lots; and generating a release schedule for each of the non-designated lots into one or more operations of the set of sequential operations; generating a release schedule for each of the designated lots into each operation of set of sequential operations such that for each designated lot a total amount of time measured from completion of a first operation of the set of sequential operations through start of a last operation of the set of sequential operations does not exceed a target amount of time for the designated lots.

Method of release and product flow management for a manufacturing facility

Method, system and program product for planning production for complementary demands are disclosed. In one embodiment, a method includes obtaining complementary demand values including at least one daily going rate (DGR) demand and a service demand; running a first planning production model in which the at least one DGR demand is included and the service demand is excluded; and running a second planning production model in which DGR related variables are fixed to values determined in the first planning production model and the service demand is included. Demands that are only considered by one of the planning production models are considered complementary demands.

Planning production for complementary demands

The invention comprises a method for achieving consideration of preemptive priorities within a supply chain optimization model. More specifically, the invention provides a method of allocating resources to a hierarchy of demand priorities in a linear programming production planning system. In particular, the invention aggregates the demand priorities into different priority groups and allocates the resources to the highest priority group of demand priorities using a first linear programming model. Next, the invention allocates remaining resources to the next highest priority group of demand priorities using a second linear programming model. The second linear programming model uses results from the first linear programming model. The invention continues this process by iteratively repeating the process of allocating remaining resources to the remaining groups of demand priorities, in order of priority. The system and method were employed to integrate the consideration of preemptive prioritization of customer demands with an advanced planning system for optimizing established planning objectives (e.g. customer service, short lead times, low inventory, and prioritized allocation of supply and capacity) to compute a feasible production plan for the division.

Method for considering hierarchical preemptive demand priorities in a supply chain optimization model

The invention provides a method of rescheduling timing of when items on purchase orders are scheduled to be received in a linear programming production planning system. This methodology performs a pre-processing rescheduling of the timing of purchase order receipts into the earliest time period allowable in a pre-processing step. After this pre-processing, the invention solves the core production planning system equations using the rescheduled purchase order receipts. Then, the invention performs post-processing rescheduling, which sorts the purchase order receipts according to rescheduling flexibility, and subsequently sequentially reschedules the timing of each of the purchase order receipts in the order established by the sorting process. This process of sequentially rescheduling reschedules the timing of purchase order receipts into the latest time period allowable.

Method for purchase order rescheduling in a linear program

A method, system, and program storage device for implementing the method of controlling a manufacturing system, wherein the method comprises providing a plurality of workpieces to be processed on a processing tool, the plurality of workpieces located at processing stations prior to the processing tool, determining auxiliary equipment allocation needs for the processing tool based on characteristics associated with the plurality of workpieces prior to the workpieces arriving at the processing tool, and sending auxiliary equipment to the processing tool based on the allocation needs prior to the workpieces arriving at the processing tool. According to an embodiment of the invention, the processing tool comprises a photolithographic system, the auxiliary equipment comprises a reticle, and the plurality of workpieces comprise semiconductor substrates.

Method and system for intelligent automated reticle managment

The invention disclosed comprises a method for encouraging fair sharing of limited material inventory and capacity between multiple customers when creating a production plan the invention allocates resources among competing demands in a linear programming production planning system by first classifying the demands into fair share sets, wherein all demands within each set have the same priority, calculating the cumulative demand for each resource within each set, and then allocating the resources to the demands in order of fair share set priority. If, during the allocating process, the supply of a given resource cannot satisfy a given cumulative demand of a given set, the given resource is allocated proportionally (e.g., evenly or according to usage proportions) among all demands that contribute to the given cumulative demand within the given set. This is an advanced planning system for optimizing established planning objectives (e.g., customer service, short lead times, low inventory, and prioritized allocation of supply and capacity) to compute a feasible production plan for the enterprise.

Method for fair sharing limited resources between multiple customers

A method, apparatus, and computer program product for organizing hierarchical information according to a defined objective.

Method, apparatus and computer program product for organizing hierarchical information

Method for simultaneously considering customer support dates and customer request dates

A method of iterative negotiation for improved production planning between one or more purchasers and suppliers in a supply chain. The method includes a purchaser in a supply chain generating a request schedule that is communicated to a supplier. In response to the request schedule the supplier generates a commit schedule and communicates it back to the purchaser. Through the iterative negotiation process (ask-answer) one or more interpolation constraints are generated based on the supplier's commit schedules. Upon completion of the ask-answer process purchaser solves a final advanced planning system (APS) based on said one or more interpolation constraints and generates a final production plan. The invention can be employed to integrate the collaboration among purchasers and suppliers with an advanced planning system for optimizing established planning objectives (e.g. customer service, short lead times, low inventory, and prioritized allocation of supply and capacity).

System for and method of interpolation for supply chain planning

A method and system for determining a plurality of coefficients of an objective function of a mathematical programming model. Attributes of the model are identified. A first set of coefficient values determining a first solution and initially representing the plurality of coefficients is determined by employing a specified ranking of the attributes. A prevailing solution is initialized to the first solution. Additional sets of coefficient values are generated, each set determining a corresponding additional solution of the model. The additional solutions are evaluated (e.g., by the Analytic Hierarchy Process) to provide a ranking of the solutions, where the ranking is dependent upon the attributes. The ranking of the additional solutions is used to select a second solution. The prevailing solution is set to the second solution if the second solution exceeds a sum of the prevailing solution and a specified tolerance.

Method, system and program product for determining objective function coefficients of a mathematical programming model

Disclosed is a method of controlling a manufacturing system. The invention automatically monitors current levels of partially completed products waiting to be processed by a tool (or group of tools) and determines whether the current levels exceed a predetermined limit. If the current levels do exceed the predetermined limit, the invention performs an optimization process. However, if the current levels do not exceed the predetermined limit, the invention performs a dispatching process. In this dispatching process, the invention automatically projects future levels of partially completed products that will be supplied to the tool to identify a future work-in-process (WIP) bubble. The WIP bubble occurs when larger than normal amounts of partially completed products are supplied to the tool. The invention automatically adjusts the operating parameters of the tool based upon both the current levels and the future levels.

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Winooski, VT, United States of America

Brian Trevor Denton