high mix manufacturing

 

Fujitsu Compound Semiconductors, Inc.

 DEHART CONSULTING has structured a strategic and innovative relationship between Fujitsu's corporate entity in Japan, its US counterpart in San Jose, and a foundry supplier in southern California that will serve as the foundation of a world class domestic operation... 


Gene Brannock, Executive Vice President Fujitsu Compound Semiconductor, Inc.

Vortex Introduction

The time-based demand-pull system (“demand-pull system”) technology of the described demand-pull system provides an implementation of demand-pull scheduling for various production operations/systems/factories.  It works in conjunction with a Material Resource Planning (MRP) or Enterprise Resource Planning (ERP) system, which creates production WOs and houses associated data, such as workflows and operational standard hours, to pull work through a factory with results similar to that of POLCA.

The subject demand-pull system pulls work into a downstream WC by matching the Flow Time of the WO to the Need Time of the downstream WC.  Need Time is the time at which the downstream WC will be ready to process the WO, and Flow Time is the time it will take the WO to reach the downstream WC.  Further definitions of terminology used in this document may be found in the Table of Definitions.  Matching these two values results in seamless flow and reduced inventory.  While this may be simple in concept, the complexity of work flow in high-variety environments and the dynamic nature of their production activities, results in overwhelming execution difficulty without the aid of computing hardware and software.

Using data from MRP that is introduced into the demand-pull system with the WOs, as well as data that is created internally, the demand-pull system is able to "reach back" from a particular WC for work from upstream operations and identify exactly which WO should be processed and when.  It does this by analyzing the WOs in the queues at each upstream WC, identifying the highest priority WO, computing its arrival time at the subject WC, and then authorizing the WO to be processed, if its arrival time at the subject WC matches (or exceeds) the time at which the subject WC will be ready to begin work on it.  Matching the Flow Time of the next WO to be authorized with the Need Time of its downstream WC assures that work arrives just-in-time.  This demand-pull system describes this method.

  • DCI Introduces Vortex Demand-Pull Technology +

    Since the early 1980's, the benefits of producing a given production volume throughput with the minimum amount of inventory have been well documented.  Beginning with the Just-in-Time methodologies, using Kanban cards for inventory replenishment, to Demand Flow methodologies,



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  • Vortex Introduction +

    The time-based demand-pull system (“demand-pull system”) technology of the described demand-pull system provides an implementation of demand-pull scheduling for various production operations/systems/factories.  It works in conjunction with a Material Resource Planning (MRP) or Enterprise Resource Planning (ERP) system, which creates production WOs and houses associated data, such as workflows and operational standard hours, to pull work through a factory with results similar to that of POLCA. 



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  • Production Priority-setting Examples +

        There are numerous methods of setting priorities in a production environment, too numerous to discuss in total in this paper, but some of the more prevalent methods are discussed below.



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  • First Authorized - First Processed Work Flow +

        When looking at work flow through a factory from the perspective of minimizing cycle time and honoring demand-pull policies, work should be processed on a first authorized, first processed (FAFP) basis. In other words, once a WO has been authorized within a WC’s queue, it should be pulled into production on a FAFP basis.  Deviating from this policy can result in an increase in the average cycle time, unless batching of WOs will reduce their aggregate cycle times due to machine capacity.  For an example of the latter situation, a machine may be capable of simultaneously processing ten pieces, and if there are two five-piece (or fewer) WOs, they could both be processed at the same time to reduce their aggregate cycle time, improve efficiency and maximize capacity.  



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  • Demand-Based Production from a Flow-Time Versus Need-Time Perspective +

    From a flow-time perspective, Work Orders should arrive in a Work Center's queue at precisely the time when they are needed to be worked on.  This minimizes both production cycle-time and inventory investment. The desired time for the next WO to arrive for processing is when the currently-authorized work in a WC and its upstream-adjacent (UA) WCs has been started into the WC and cleared the first operation in the WCs routing. This assumes that demand exists for the WO at the next downstream work cell.



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  • Examples of the Vortex Authorization Process +

    The examples set forth in the table below illustrate the WO authorization process resulting from the pull-test in different circumstances.  In all the examples, a set of WCs such as shown in the following Figure is used.  There are two WCs (WC 130 and WC 135) that feed into a third WC (WC 145) and the downstream WC (WC 145) is presumed to be healthy (reference the discussion of Work Center Performance Testing) so that the pull-testing for this WC is active. 



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  • Calculating Flow Time in a Work Center +

    Using Standard Labor/Machine Processing Hours
    In the case where all units in a WO are processed as a discrete set, the Flow Time of a WO in a WC is equal to the Standard Process Hours of the WO.



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  • Demand-Based Production from a Work-Volume Perspective +

    When looking at authorizing work in upstream stages of production, the traditional Kanban system establishes quantity buffers, or queues, at each WC. Then when the buffer quantity hits a minimum value (the Queue Policy), the Kanban card is returned to its originating WC for replenishment. 



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  • Table of Definitions +

    The following is a Table of Definitions for the articles describing the Vortex technology.



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  • An Optimum Queue Policy +

    The formulae from Demand-Based Production from a Flow-Time Versus Need-Time Perspective and Demand-Based Production from a Work-Volume Perspective can now be combined to solve for the Queue Policy (XN).



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  • An Automated Demand-Pull System Embodiment +

    The Figures below illustrate an embodiment of the demand-pull system, which can be implemented using a software system with a database.  In this embodiment, a .NET service bus and MSSQL database running on a networked Microsoft Windows server are connected via the local area network (LAN) to individual clients in the various WCs. 



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  • Comparison of Time-Based Demand-Pull versus POLCA +

    POLCA (Paired Overlapping Loops of Cards with Authorization) is a prior art system to produce solutions to the application addressed herein, that is, demand-based shop floor control in a high mix, or high variety, production environment. 



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  • Vortex Shop Floor Control for Discrete Manufacturing +

    Is your manufacturing environment order-driven? Do you Engineer-to-Order or Customize-to-Order? Do your spaghetti diagrams look more like a network than continuous flow? If you struggle with production cycle-times that are too long and inventories that are too high, we have a solution!


    Introducing Vortex, a Shop Floor Control system designed to minimize your production cycle time and reduce inventory. Vortex works to pull production through your factory exactly when it’s needed! It predicts when a work center will be in need of more work, identifies the highest priority batch in all upstream work centers, and then authorizes the batch to be started just at the right time for it to reach the work center exactly when it is needed.


    Upstream work is only released if there is downstream demand, thus implementing one of the basic tenets of Lean Manufacturing – demand-pull production – in the high-variety, order-driven factory.


    Sounds simple, right?  In theory, yes.  However, if you’re talking dozens of work centers, dozens of different work flows and varying batches of sizes and flow times – predicting the time at which more work than is currently authorized for production will be needed can very quickly get complicated – the real-time calculations piling up pretty fast.

     
    Vortex streamlines the thousands of computations with a patent-pending algorithm, which works not only to synthesize all the math, but also integrate those solutions directly into your production system.


    Vortex’s modern, standards-based API is compatible with most ERP and Shop Floor Control systems.  The fully featured API allows your ERP and other internal systems to always stay up-to-date with the status of work on the shop floor. Vortex relies on your existing ERP system to create Work Orders according to your existing planning policies and inject them into the system through the API.  From there, Vortex handles the Starts into each work center based on demand-pull policies – minimizing both cycle-time and Work-in-Process inventories.  


    Check out our demo based on the following 5 products with individual work flows through 10 work centers. To view the demo, please click the link on this page - or drop us a line and we will take you for the tour.



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