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INTEGRATING MRP WITH KANBAN/PULL SYSTEMS
by
Uday S. Karmarkar
Working Paper Series No. QM8615
June 1986
Center for Manufacturing and Operations Management The Graduate School of Management
The University of Rochester
..
INTEGRATING MRP WITH KANBAN/PULL SYSTEMS
Uday S. Karmarkar
Center for Manufacturing and Operations Management Graduate School of Management
University of Rochester
ABSTRACT
Push manufacturing systems like MRP and pull systems like Kanban, are
sometimes thought of as representing antithetical approaches to controlling
production. However. these approaches involve principles that are not
incompatible. A hybrid system is described that combines MRP at the
plant-wide level with a Kanban approach at the loca] cell leve]. The
calculations required in the MRP system are simplified. but the ability to
utilize advance information about demand is retained. Simultaneously, the
reactive abilities and the appealing incentive structure of the Kanban system
are incorporated in the hybrid system. This approach is appropriate for a
repetitive batch manufacturing environment. with part fabrication. subassembly
and assembly stages.
INTEGRATING MRP WITH KANBAN/PULL SYSTEMS
Uday S. Karmarkar Center for Manufacturing and Operations Management
Graduate School of Management University of Rochester
.. Introduction
Push systems of .anufacturing control, such as Material Requirement
Planning (MRP) were originally seen as improving on pull systems of the Order
Point, Order Quantity type. Unlike the latter, MRP s~stems take actual
demands into account, and trigger production of "dependent" demand items in
the required quantities, and at the required times as estimated by the lead
time offsetting procedure. While this approach sounds suspiciously like a JIT
system, it does not appear to work that way in practice. A problem with MRP
logic is that the dependence of production lead times on shop conditions,
batch sizing and release timing is not recognized. Instead, lead times are
taken to be given exogenously as fixed para.eters. This inability of MRP to
relate lead times to capacity loading and order release policies can lead to
poor on-time, work-in-process and lead time performance.
Despite the seeming inefficiencies inherent in pull systems, due to their
lack of use of information about demands, the Japanese Kanban system appears
to function effectively 1n certain production environ.ents. While, pull
systems are not, from a definitional point of view "just-in-ti.e", they are so
effective as to be identified closely with JIT methods. At least one reason
for the success of these systems is that they create an informational and
organizational environment, where the role of production lead times becomes
obvious, and where there are incentives to control and reduce lead times.
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Descriptions of the working of Kanban systems have been given by Hall
(1983), Monden (1983) and Schoenberger (1983), who also describe other aspects
of Japanese manufacturing strategy and JIT techniques. Karmarkar (1986)
discusses the complementarity between Kanban systems, and other aspects of
manufacturing strategy, and relates the Kanban approach to other pull control
techniques. The dynamics of Kanban systems have been discussed by Groenevelt
and Karmarkar (1986), Huang,Rees and Taylor (1983), Karaarkar and Kekre
(1986), and Kimura and Terada (1981). The comparative effectiveness of push
and pull systems has been discussed by Kekre (1985), and Karmarkar and
Shivdasani (1986) correlate the use of push and pull .anufacturing control
techniques with the characteristics of the physical process being controlled.
Finally, Karmarkar (1986) discusses the evolution of push and pUll systems.
and argues that key features of both are captured in hybrid control systems
that combine aspects of the two approaches. Groenevelt and Karmarkar (1986a,
1986b) develop techniques for forecast-driven Kanban systems that adapt
dynamically to changing demand conditions, and describe an application.
In this paper we discuss the design and operation of a hybrid control
system for a batch .anufacturing environment. The overall facility is
controlled by an MRP approach, which computes requireMents at the item and
subassembly level from a master schedule. Locally, the facility is organized
into .anufacturing cells which are each operated using Kanban .ethods. The
difference with the conventional approach is that the MRP syste. provides each
cell with future production requirements for that cell. This information is
used to change the parameters of the Kanban control scheme. The basic
approach is to control the card count within the Kanban system on the basis of
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the requirements generated by the MRP system. An extension of this approach
is to also control the production batch sizes in the cell based on the
information provided by the MRP system.
Requirement Triggered Kanbans
The cards (Kanbans) in a Kanban pull system play the role of work orders.
That is, the release of a card due to withdrawal from inventory, authorizes
production of a replenishment batch. The quantity to be produced is also
indicated on the card. The mechanism of the release timing process -- by the
physical withdrawal of output inventories -- is what categorizes a Kanban
system as a pull system. This pull release Mechanism does not use any
information about future demands. and production is not triggered for any
particular future requirement. As a result. even if information on impending
variations in demand is available well in advance. pull systems in their
pristine form cannot incorporate it in their operation.
By contrast. an MRP system directly releases work orders by computing net
requirements for each item. by combining requirements into production or
release lot sizes, and then by determining the release time for these planned
orders by offsetting the order based on production lead time data. The timing
of production thus depends directly on the lead times assumed by the MRP
system. If these lead times are not accurate. the resulting effect on
production timing can cause excess inventories or missed due dates, depending
on the nature of the errors.
In the hybrid system, MRP is still used to compute gross requirements for
each item and subasseMbly, but not net requirements. These gross requirements• are used to set the number of cards in each cell. However, they do not
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directly determine the timing of production; that is still left to the local
control of each cell. As a result, the total material inventories in the cell
are controlled by the cell superv i ~('J. who determines when a card ",i 11
•actually be released for production.
Let us suppose for a moment that the MRP system had precise knowledge of
what the lead times would be at the time that each unit was produced. This
lead time would include queue time at each work center or cell. The total
quantity associated with cards and in finished inventory in a cell at any time
must equal the production required from the cell in the next lead time
interval. To see this note that a card just released to the cell will be
required after a lead time interval. Furthermore, any card released less than
a lead time interval in the past would not as yet be removed from the cell.
This concept is analogous to the base stock system (see Karmarkar. 1986;
Groenevelt and Karmarkar, 1986 for a discussion).
Now if the lead time at each work center for each order or lot were
actually known exactly, the finished inventory in the system would be zero,
the cards in the system would correspond to demand over the next lead time
interval, and items would be produced for finished inventory just as they were
demanded. However, in practice such clairvoyance has not been present in MRP
implementations. Of course, the underlying problem is that lead times are a
aoving target, constantly changing with shop load, job mix and with random
events. As a result, we can assume that the lead times in the MRP system, are
as usual inflated to cover the variability and ignorance about actual lead
times. A card will be released to a work center at a time that is a safe
estimate of a lead time away from the actual requirement for the finished
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material. This gives the cell supervisor or mana2er some leeway to decide on
the actual time that a card authorized by the MRP system can be physically
released to the floor.
To summarize, the conceptual working of the system is as follows: master
schedules are the input to MRP computations that generate gross requirements
by item. offset by estimated lead times. The gross requirements determine the
cards released to authorize production of each item to the corresponding cell
or work center. The total number of cards in a work center at any given time.
whether in queue, in process or in finished inventory, are equal to the gross
requirements for that work center over the lead time interval for the work
center, as estimated from the lead time information available to the MRP
system. While that is the "authorized" quantity of cards, the Dlanageror
supervisor of the cell may choose to use a smaller number of cards to be
active at any given time. Of course, if this can be done consistently, it
implies that the lead times used in the MRP computations are too large.
This entire approach is most appropriate for repetitive batch
.anufacturing environments with parts and raw material purchasing, parts
fabrication, subassembly and assembly production stages. The cell
organization with pull control can be employed in both fabrication and
subasseDlbly stages. The approach is not appropriate for a custom or
en2ineered product environ.ent or for a custo.er order oriented system. In
the latter case, the identification of production lots with particular
customer orders can only be done at the final assembly stage. Customer orders
cannot be identified with particular production batches at other stages very
precisely, since there is not specific batch or production work order to bp
associated with an end item order. Note that kanban cards are "generic" and
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do not have any special identification that would allow pegging to customer
orders. Of course, a system could be devised that would generate cards with
specific pegging information associated with them. However, the added costs
for information processing and implementation should be recognized. The major
purpose of pegging is to permit expediting of particular orders. The pull ,
system approach is predicated on making the production system so reactive and
reliable that expediting is not required. Or rather, the detection of
specific order related problems is replaced by the rapid identification of
underlying process problems.
The detailed operation of the system involves the precise rules for
generation and removal of cards. Cards are generated by the MRP system, but
may also be added locally. In particular buffer inventories and compensation
for yield, scrap and rework can be handled through local control of cards.
These details and modifications are discussed in a later section.
The Benefits from Hybrid Systems
The rationale behind the hybrid approach is that the useful features of
both push and pull systems can be melded into one system. Broadly, the push
features permit the effective use of detailed knowledge about demand
variations. The pull features provide the appropriate incentives at the cell
level, and .ake use of the detailed information available at the local level,
without trying to collect that information in a centralized system. There are
several specifically identifiable advantages to this hybrid scheme.
Local Inventory Manage.ent. A major role of a conventional MRP system is
inventory management. The quantities (and perhaps location) of on-hand •
inventories at all production stages are controlled by the system. Such an
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approach removes responsibility of controlling and maintaining inventories
from the local cell level. In the hybrid system, inventories in a cell.
whether of raw material or finished parts. are the responsibility of that
cell. As a result, there is no need to impose discipline about inventory
.anagement from "above" or to monitor inventory levels and locations. It is
in the cell supervisor's interest to see that inventory levels and'locations
are known and controlled. It should be noted that there are situations where
inventory tracking is required because lot identities must be maintained. For
example, in batch chemical production. each batch may have its own composition
which has to be recorded and the batch located. Centralization of this lot
tracking requirement may be the most efficient approach. especially since the
information may be required at separate points in the plant and process.
Reduction of Shop Floor Data Collection. Since material and inventory
manage.ent on the floor is decentralized. data on inventory levels and
locations does not have to be collected and centrally maintained.
Furthermore. individual orders do not have to be tracked. since the
responsibility of supplying a succeeding cell promptly. lies with the cell
.anager. Recall that this system is thus most appropriate for a repetitive
batch flow environment. rather than for engineered products. customized
products or customer order oriented production.
It should be noted that while current shop status information does not
have to be collected. shop performance over a given period does have to be
.easured. Among the measurements that should be made are cell lead times,
average work-in-process levels, scrap and rework levels, backorder and
shortage incidence. and setup and processing times. Many of these• measurements can be conveniently done using the card system itself.
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Reduction of MRP Computations. Since inventory management is a local
function. and since the incremental quantities produced are at the discretion
of the cell. Certain computations become unnecessary. In particular. netting
of requirements is not required; in effect it is done locally by determining
which of the authorized cards are already covered by available material.
Purthermore. pegging is not required and the associated data management
overhead can be eliminated. Even if pegging is to be implemented, MRP
generated cards can be pegged directly to end item orders or the end item
production schedule. Stage by stage pegging is not possible. and should not
be necessary.
MRP computations in this system are thus reduced to simply converting end
item production schedules to gross requirements for each item. offsetting the
gross requirements by total lead time for that item. and then computing the
corresponding card count or equivalently a card generation schedule. Note
that this can be done without a level by level BOM explosion. and a single
level BOM is adequate.
Reactive Ability. Since the cell level is controlled with a pull
approach, the manufacturing system is able to react to unplanned events by
local adaptation. Por example. in a pure push system, the loss of part
inventory due to damage would require the generation of a new order from the
MRP system. The loss would only be discovered at a cycle count point or when
the inventory was found to be unavailable for use. In the pull framework.
inventory responsibility lies with each cell. and there are incentives to
continually monitor inventories. A loss of inventory would tend to be noted
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immediately, and replacement initiated. Note that this causes unplanned use
of incoming material and the card generation scheme must be modified to
account for the additional production.
Local Incentives for Performance Improvement. An important feature of
the Kanban environment, is that there are incentives at the local level for
lead time and WIP reduction, and quick response to contingencies. These
incentives are lost in an MRP or push environment, because leadtimes are
planned by the system. and allowance is made for leadtime variability in the
release policy. As a result. there is no benefit and no reward for reducing
production lead times, or equivalently, work-in-process. In this hybrid
system, the cell level incentive structure can be maintained by assigning
responsibility for inventory levels to the cell, and by clarifying that the
cards released by the MRP system are authorization to produce and not
production releases in the usual sense. The cell manager has the option of
holding a card as late as possible, to reduce the importation of raw material
into the cell.
In addition to the incentives, it is also important that the supervisor
of the cell has the authority to make the decisions on layout, equipment
choice, labor assignment. engineering improvements and so on, that can effect
setup reduction, lead time reduction and flexibility improvements in the cell.
Perforaance Measurement. The cell organization that is maintained in the
systea requires the measurement of manufacturing performance at the cell
level. Lead time monitoring is especially important. Production lead time in
the cell is measured as the average time taken from the time that a card is
posted in the cell to the time that finished material corresponding to that
card is available for use by succeeding cells. The use of cards generated for
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each cell simplifies this measurement task. Furthermore, as lead times are
reduced. there is immediate feedback to the central MRP system. since the
release time of cards by the system can be compared to the time that the cards
are actually released to the cell.
Implementation and Modifications
One possible realization of the card generation will be described here.
It is important to note that special features of particular environments may
require modification of the basic process. Some of these modifications will
be described later in this section. It will be assumed that the plant
includes some part fabrication. subassembly operations, and final assembly of
end items.
Given a master schedule for final items, the MRP computations are
simplified to computation of gross requirements only. As described in the
previous section. inventory management and netting is not done at the plant
level but at the local, cell level. The pattern of gross requirements
determines the card count in the cell: the quantity of material on order in a
cell at any point is equal to the requirements on the cell in a period equal
to the production lead time for the cell. The gross requirements for each
item are suamed from the current time to a horizon equal to the lead time for
the cell. This number is then converted into the nu.ber of cards released to
the cell. by dividing by the batch size associated with each card. A rounding
procedure is used to give an integer number of cards and the difference
between actual and rounded values is either carried forward or subtracted from
the next requirement as appropriate.
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..
This computation gives the total number of cards active in the cell at
any time. This number will change with each period so that cards have to be
added or· subtracted accordingly. An alternative way to look at this is that
the change in the number of cards in each period is obtained by subtracting
cards for the gross requirement in the current period, and adding cards for
the gross requirement in the period that is one lead time away.
It is instructive to compare this scheme with the approach used in rate
oriented production as in the automotive industry. Typically there too,
requirements are not netted; rather the cumulative requirement for each item
is computed from gross requirement. Production then "chases" the cumulative
requirement. The problem with this approach is that the current load on a
shop is not apparent from the system. In the hybrid system proposed here.
this load is precisely the gross requirement (demand) over the succeeding lead
time; which is communicated as the "open" number of cards or equivalently the
quantity "on order".
The scheme described thus far has the advantage of simplicity in
coaputations. However, it has certain limitations. First of all it assumes
that production lead times for each cell are known to the central MRP system.
In general. these lead times cannot be accurately known centrally because they
change with shop loading. Of course, unlike the usual MRP procedure, these
lead tiaes determine card quantities and not actual production timing.
Nevertheless, if lead times change substantially over time, the number of
cards generated may not be correct. Secondly. the central system assumes that
there is no uncertainty in production. If in fact, there is the potential for
quality problems, yield and rework. late material deliveries and so on. the
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number of cards authorized at any time lIay not be correct. Certain
modifications to the basic system can ameliorate some of these problems. We
describe two such 1I0difications.
Consider the lead time issue: the problem here is that if lead times at
sOlie point. are lIuch longer than "norllal" due to a high load on the shop. the
number of cards generated will be sllaller than necessary. In a conventional
MRP system. the COII.on response to this variability in lead times is to
inflate planned lead times sufficiently to cover the variations.
Unfortunately, this means that most of the tille, the lead time allowed is .uch
longer than is necessary and as a result. work-in-process and finished
inventories are increased. What is more, because the lead time data is
maintained in a centralized data base, there is no incentive to correct
inflated figures. Lead times once increased, tend to stay high. In the
hybrid system. this situation can be avoided to a considerable extent. First
of all, even if lead times in the MRP system are inflated. each cell has the
option of not putting authorized cards into production immediately. Since
releasing cards to production raises inventories in the cell, there are
incentives to delay production as far as possible. In addition, the basic
card generation system can be modified by allowing cell managers to generate
extra cards. For example, if a cell lIanager realizes that lead times are
likely to increase because of increased load on the cell or because of lIachine
failure, absenteeism or other losses of production capacity. the lIanager can
recognize that the number of cards needed in the cell is larger to cover the
longer lead time. The lIanager should have the ability to generate such cards
and it is useful to have the extra cards (electronic or otherwise)
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distinguished by color or some other method. Tracking the lead time and time
in finished inventory experienced by these cards will measure the
effectiveness of this system.
In the preceding example, there is no change in the total cumulative
quantity produced. The extra cards are produced to account for lead time
variability, and create a larger pool of work-in-progress (on order) to allow
for the increase in lead times due to special conditions that are foreseen by
a cell manager. The same local card generation scheme may also be used by a
cell manager to create safety or buffer stocks to protect against unforeseen
machine failure or unforeseen short term variations in demand. The important
point to note here is that these buffer or safety stocks are locally created
in response to local problems. Furthermore, since the manager bears the costs
of the added inventories, there is an incentive to reduce these stocks as much
as possible, and still maintain service levels. This .echanism is very
different from centrally determined safety stocks and safety times, where
there is the continuing risk of institutionalizing errors in estimation.
Now consider the very different problem of accounting for imperfect
yields, quality problems, and inventory losses. The issue here is that unlike
the former case, here total production in the cell, and in all parts of the
production system supplying the cell, must be increased to account for the
lost production. In effect, the total quantity demanded over the current lead
time interval, for all supplying cells is increased. There are two ways in
which this situation can be handled. One is to simply depend on safety stocks
held in each cell against downstream production loss problems. This is not
the best approach, because the point of protection is removed from the point
at which the problem occurred and managers who have no control over the
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proble~ are being penalized by having to hold inventories. An alternative
approach is to require that extra production to cover losses should require
generation of extra cards. These cards would be produced for all suppliers of
the cell in which the loss occurred, and would be correspondingly marked. Of
course, new purchase orders to account for lost .aterial must be generated,
and this system would also create these new orders. The drawback of this
system is that it imposes a high administrative cost on the system. It would
be most efficient to produce the extra cards centrally, on notification from
the cell. Such a procedure would allow efficient (net change) processing of
the extra ~aterial, and would simplify maintaining data on yield and quality
performance.
Summary
This paper has described a hybrid push/pull system embodying elements of
both kinds of control system. An MRP system without netting is used for
material planning and for generating purchase orders. The manufacturing
process is organized as cells which are operated by a Kanban system, using
cards or some other signalling or triggering device. Unlike the typical
Kanban system, the number of cards in the system is varied dynamically. Cards
are generated by the MRP system, based on the gross requirements for each
cell, over a cell production lead time interval. Thus, the cell is able to
react to changing demand and load conditions by making use of advance
information about planned orders. This is the "push" part of the process. At
the same time, production activity is triggered by the cards and the
incentives in the system are local as in a pull system. In particular,
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inventory is locally "owned" and managed, and safety or buffer stocks are set
locally. This hybrid approach is suitable for repetitive batch production
where lot identity does not have to be maintained .
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REFERENCES
Groenevelt. H., and Karmarkar. U. S. (1986a), "Flexible Dynamic Kanban Systems: A Case Study". Graduate School of Management, Working Paper No. QM • University of Rochester, Rochester, New York.
Groenevelt, H.• and Karmarkar. U. S. (1986b), "Forecast Driven Kanban Systems", Graduate School of Manage.ent, Working Paper No. QM University of Rochester, Rochester, New York.
Hall, W. R. (1983), "Zero Inventories", Dow Jones, Irwin, Illinois.
Huang, P. Y., Rees, L. P. and Taylor, B. W. (1983), "A Si.ulation Analysis of the Japanese Just-In-Time Technique (with Kanbans) for a Multiline, Multistage Production System", Decision Sciences, Vol 14, pp. 326-344.
Karmarkar, U. S. (1986a), "Push, Pull and Hybrid Control Schemes", Graduate School of Management. Working Paper No. QM8614, University of Rochester, Rochester, New York.
Karmarkar, U. S. (1986b), "Kanban Systems", Graduate School of Management, Working Paper No. QM8612, University of Rochester, Rochester, New York.
Karmarkar, U. S., and Kekre, S. (1986), "Batching Policy in Kanban Systems", Graduate School of Management, Working Paper No. QM ,University of Rochester, Rochester, New York.
Kar.arkar, U. S. and Shivdasani, I. M. (1986), "Alternatives for Batch Manufacturing Control", Graduate School of Management, Working Paper No. M8613, University of Rochester, Rochester, New York.
Kekre, S. (1984), "Management of Job Shops", Ph.D. Thesis, Graduate School of Management, University of Rochester, Rochester, New York.
Ki.ura, O. and Terada, H. (1981). "Design and Analysis of Pull System, a Method of Multi-Stage Production Control", International Journal of Production Research, Vol. 19, No.3, pp. 241-253.
Monden, Y. (1983), Toyota Production System, Industrial Engineering and Management Press. Norcross, Georgia.
Schonberger, R. J. (1983). "Applications of Single-Card and Dual-Card Kanban" , Interfaces, Vol. 13, No.4, pp. 56-67.
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