Theory of Constraints
Synchronous Manufacturing
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Introduction
• Synchronized manufacturing (SM) is any systematic way that attempts to move material quickly and smoothly through the various resources of the plant in concert with market demand
• Synchronized manufacturing refers to the entire production system working together in harmony to achieve the goals of the firm
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Hockey-Stick Phenomenon
• In most organizations there is a rush to meet quotas at the end of each month (or other time period)
• This rush results in the expediting of parts through the system
• Expediting of parts results in confusion, delays, extra setups, and usually overtime expenses
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Hockey-Stick Phenomenon
• The end-of-period rush!
Period1 2 3 4
Output($)
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Hockey-Stick Phenomenon • Problem arises because two sets of
measurements are being used– At beginning of month, cost accounting
efficiency measures are used• High efficiencies, minimal setups, etc.
– At the end of the month, financial performance measures are used
• Net profit, return on investment (ROI) and cash flow
• To achieve these two types of measurement, high levels of inventory are needed which augments the problem even further
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The Goal
• The goal of the firm is to make money both now and in the future– What about the following:
• Providing jobs
• Consuming raw materials
• Increasing sales
• Increasing market share
• Developing technology
• Producing high quality products
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Measuring the Goal
• Two sets of performance measures are used to determine how well the company is meeting its goal (making money):– Financial
• Higher level measures
– Operational• Shop floor measures
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Financial Measures
• 1. Net Profits– An absolute measurement of making money– Net profit has no meaning until we know how
much investment it took to generate it, thus, we need to index it as a return on investment
• 2. Return on Investment– A relative measurement
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Financial Measures
• 3. Cash Flow– A survival measurement– Cash flow is important since cash is necessary
to pay bills for day-to-day operations; without cash, the firm will go bankrupt even though it is very sound in normal accounting terms
• We need all three of these measurement used together
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Financial Measures
• The financial measurements are good for telling us when we are making money, but they are inadequate in judging the impact of specific actions on the goal
• Need to bridge the gap between specific operational decisions we must make and the bottom line measurements of the entire firm
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Operational Measures
• Throughput– The rate at which the system generates money
through sales
• Inventory– All the money the system invests in purchasing
things the system intends to sell
• Operating Expense– All the money the system spends in turning
inventory into throughput
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Operational Measures
NET PROFIT RETURN ON INVESTMENT
CASH FLOW
THROUGHPUT INVENTORY OPERATINGEXPENSE
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Operational Measures
NET PROFIT RETURN ON INVESTMENT
CASH FLOW
THROUGHPUT INVENTORY OPERATINGEXPENSE
The Indirect Impact of Inventory and Carrying Charges
CARRYINGCHARGES
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Operational Measures• The indirect impact of inventory on the three
bottom line measurements is typically estimated through the use of carrying charges
• Lowering inventory reduces a number of operating expenses, such as:– interest charges– storage space– scrap– obsolescence– material handling– rework
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The Goal Revisited
• If we examine the operational measures, we can restate the goal in their terms:
The Goal of a firm is to increase throughput while simultaneously reducing inventory and reducing operating expense
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Productivity
• Productivity– All the actions that bring a company closer to
its goals
• Does not guarantee profitability– Has throughput increased?– Has inventory decreased?– Have operational expenses decreased?
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Balanced vs. Unbalanced Capacity• Historically, manufacturers have tried to
balance the capacity of each resource across a sequence of processes in an attempt to match capacity with market demand– The goal was constant cycle time across all
stations
• However, synchronous manufacturing views constant workstation capacity as a bad decision– Why is this the case?
• Let’s consider the balanced capacity situation
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A C D25
B E F50 30 30 3015
• Consider a Balanced Capacity:– A simple process line with several stations
– The output rate for the line has been established• Production people try to make the capacities of all
stations the same by adjusting machines or equipment used, workloads, skills, and type of labor assigned, tools used, overtime, etc...
Balanced vs. Unbalanced Capacity
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• Balanced Capacity (continued)– This would be possible only if the output times
of all stations were constant or had a very narrow distribution
– A normal variation in output times causes downstream stations to have idle time when the upstream stations take longer to process materials than was originally planned
Balanced vs. Unbalanced Capacity
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F
A
A
A
B
B
B
B
B
B
C
C
C
C
C
C
D
D
D
D
D
D
D
D
D
D
E
E
E
E
E
F
F
F
F
• Balanced Capacity (continued)
Balanced vs. Unbalanced Capacity
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Balanced vs. Unbalanced Capacity
• Balanced Capacity (continued)– Conversely, when the upstream stations process
the materials in a shorter time, inventory builds up between stations
– This effect is called statistical variation, and it is cumulative
– The only way that this variation can be smoothed out is by increasing work in process to absorb the variation, or increase the capacities of each resource downstream
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Balanced vs. Unbalanced Capacity
• Unbalanced Capacity– Rather than balancing capacities, the flow of
product through the system should be balanced– The rule with capacities is that capacities within
the process sequence should not be balanced to the same level
– Rather, attempts should be made to balance the flow of product through the system
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Process Time (B)Process Time (A)
Dependent Events and Statistical Fluctuations
• Dependent Events– In a process sequence, the ability to do the next
process is dependent on the previous one
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Dependent Events and Statistical Fluctuations
• Statistical Fluctuations– Normal variation about a mean– When these occur in a dependent sequence
without any inventory between workstations, there is no opportunity to achieve the average output
• When one process takes longer than average, the next process cannot make up the time
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Capacity Related Terminology• Capacity
– Available time for production
• Bottleneck– Capacity is less than demand placed on resource
• A bottleneck limits the throughput.
• Non-bottleneck– Capacity is greater than demand placed on resource
• Avoid changing a non-bottleneck into a bottleneck
• Capacity-constrained resource (CCR)– Capacity is close to demand placed on resource
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X Y Market
Case A
X YBottleneck Nonbottleneck
Demand/month 200 units 200 unitsProcess time/unit 1 hour 45 minsAvail. time/month 200 hours 200 hours
What’s Going to Happen?
• Bottleneck feeding a non-bottleneck
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What’s Going to Happen?
Y X Market
Case B
X YBottleneck Nonbottleneck
Demand/month 200 units 200 unitsProcess time/unit 1 hour 45 minsAvail. time/month 200 hours 200 hours
• Non-bottleneck feeding a bottleneck
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X Y
Assembly
MarketCase C
X YBottleneck Nonbottleneck
Demand/month 200 units 200 unitsProcess time/unit 1 hour 45 minsAvail. time/month 200 hours 200 hours
What’s Going to Happen?• Output of bottleneck and non-bottleneck
assembled into a product
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X Y
Market Market
Case D
X YBottleneck Nonbottleneck
Demand/month 200 units 200 unitsProcess time/unit 1 hour 45 minsAvail. time/month 200 hours 200 hours
What’s Going to Happen?• Bottleneck and non-bottleneck have
independent markets for their output
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Basic Manufacturing Building Blocks
• The previous four cases can be thought of as the basic building blocks for manufacturing
• A production process can be simplified into one of these four building blocks to simplify analysis and control– Group all non-bottleneck resources together and
display them as a single non-bottleneck resource
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Components of Production Cycle Time
• Setup time– the time that a part spends waiting for a
resource to be set up to work on this same part
• Process time– the time that the part is being processed
• Queue time– the time that a part waits for a resource while
the resource is busy with something else
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Components of Production Cycle Time
• Wait time– the time that a part waits not for a resource but
for another part so that they can be assembled together
• Idle time– the unused time
• the cycle time less the sum of the setup time, processing time, queue time, and wait time
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Finding the Bottleneck
• Two ways to find a bottleneck– 1. Capacity resource profile
• As examined in the simulation
– 2. Use knowledge of plant, look at the system in operation, and talk to supervisors and employees
• As seen in THE GOAL
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Bottleneck Non-bottleneck
Saving Time
A MirageAn Hour Saved For Entire Plant
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Drum-Buffer-Rope
• Drum– Control point to control flow of product
through the system– Located at the bottleneck or the CCR
• Buffer– Inventory in front of a bottleneck (time buffer)
• Rope– Communication to entry point of material to be
processed
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Drum-Buffer-Rope
CBA50 30 25
Time Buffer
F30
E30
D15 Finished
Goods
Drum
Major Capacity Constraint
RawMaterials
A Rope tying the gating operation to the buffer
Market Demand
A Rope tying Market Demand to the CCR schedule
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Drum-Buffer-Rope
• Two major constraints on a firm– The market demand for its products– The capacity of the CCR
• Thus, we need to base the schedule on the CCR by taking into account only its limited capability and the market demands that it is trying to satisfy
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Drum-Buffer-Rope
• Once the CCR’s schedule is established,– we need to determine how to schedule all the
non-constraining resources– Schedule for succeeding operations can be
derived easily• After a part has been processed at the CCR it is
scheduled to start at the next operation
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Drum-Buffer-Rope• The challenge is to schedule the preceding
operations and to protect the CCR from disturbances that might occur at the preceding resources– If disturbances at preceding operations can be
overcome in two days, then set the time buffer at three days
– Schedule the operation immediately preceding the CCR to complete the needed parts three days before they are scheduled to run at the CCR
– Then back schedule the remaining operations
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Drum-Buffer-Rope
• The procedure laid down so far will protect the throughput of the plant
• BUT, meeting customer due dates is also important and needs to be protected– Need to create a buffer of parts at final
assembly for items that do not go through the CCR to protect against disturbances in procurement and manufacturing
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Drum-Buffer-Rope
Final Assembly
Subassembly
Subassembly
CCR
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How to Beat the Drum
• A CCR limits the throughput of the plant and controls due-date performance
• Must ensure that the CCR is not scheduled to produce more than its capacity and not to waste any of its capacity by allowing any slack in its schedule
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How to Beat the Drum
• First:– Schedule forward in time form the present
• Decide what product to schedule first, second, etc...
• When the available capacity of the CCR for the first day is used up, begin scheduling the second day, etc...
• The only remaining problem is how to choose the sequence in which the various products are to be done by the CCR
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How to Beat the Drum• Customers due dates for the various
products will provide the first cut schedule
• There are four case where we may need to modify the customer due-date schedule for sequencing products through the CCR– Completion times for the various products are
greatly different– One CCR feed another CCR– Setups on the CCR– A CCR produces more than one part for the
same product
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Locating the Time Buffers
• Concentrate protection not at the origin of disturbance, but before critical operations
• Inventory of the right parts in the right quantities at the right times in front of the right operations gives high protection
• Inventory anywhere else is destructive
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Ropes
• Release and process materials according to the schedule determined by the plants constraints
• Do not release materials in order to supply work to workers, or for any other reason
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Example• The following diagram contains the product structure, routing,
and processing time information for product A. The process flows from the bottom of the diagram upward. Assume one unit of items B, C, and D are needed to make each A. The manufacturing of each item requires three operations at machine centers 1, 2, and 3. Each machine center contains only one machine. a machine setup time of 60 minutes occurs when ever a machine is switched from one operation to another (within the same item or between items)
• Design a schedule of production for each machine center that will produce 100 A’s as quickly as possible
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Example
A
B C D1 1 1
1
2
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1 2
2 3
3
B3
B2
B1
C3
C2
C1
D3
D2
D1
7
3
5
15
10
2
5
8
10
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Example• Solution:
– Identify the bottleneck machine– To keep the bottleneck busy, schedule the item
first whose lead time to the bottleneck is less than or equal to the bottleneck processing time
– Forward schedule the bottleneck– Backward schedule the other machines to
sustain the bottleneck schedule– Remember that the transfer batch size does not
have to match the process batch size
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Example• The bottleneck machine is calculated by
summing the processing times of all operations to be performed at a machine
Machine 1 Machine 2 Machine3B1 5 B2 3 C1 2B3 7 C3 15 D3 5C2 10 D2 8 D1 10
22 26* 17
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Example• Machine 2 is identified as the bottleneck, so we
schedule machine 2 first. From the product structure diagram, we see three operations that are performed at machine 2 - B2, C3, and D2. If we schedule item B first, a B will reach machine 2 every 5 minutes (since B has to be processed through machine 1 first), but B takes only 3 minutes to process at machine 2, so the bottleneck will be idle for 2 minutes of every 5 minutes. A similar result occurs if we schedule item D first on machine 2. The best alternative is to schedule item C first
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BottleneckSequence
Completion Timefor 100 A’s (mins)
Total IdleTime (min)
TotalProcessingTime (min)
C3, B2, D2 2,737 994 3,731
C3, D2, B2 3,135 1,447 4,582
Example• We will process the items in batches of 100
to match our demand requirements
– The bottleneck sequence is C3, B2, D2– Machine center 1 sequence is C2, B1, B3– Machine center 3 sequence is C1, D1, D3
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Quality Implications
• More tolerant than JIT systems– Excess capacity throughout system, except at
the bottleneck• Quality control needed before bottleneck
• Want quality assurance at each process downstream from the bottleneck to ensure passing product is not scrapped
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Batch Sizes
• What is the batch size?– One?
• Transfer batch
– Infinity?• Process batch
– Using transfer batches that are smaller than the process batch quantity causes shorter production times and less WIP inventory
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How to Treat Inventory
• The negative impact of inventory is not only in its additional carrying costs, but in– longer lead times– creating problems with engineering changes
• Dollar Days– A measurement of the value of inventory and the
time it stays within an area
(value of inventory)(number of days within a department)
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How to Treat Inventory
• Benefits from Dollar Day Measurement– Marketing
• discourages holding large amounts of finished goods inventory
– Purchasing• discourages placing large purchase orders that on
the surface appear to take advantage of quantity discounts
– Manufacturing• discourage large work in process and producing
earlier than needed
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Comparing SM to MRP
• MRP uses backward scheduling– Works backward in time from the desired
completion date (BOM explosion)
• Synchronous manufacturing uses forward scheduling– Focuses on the critical resources which are
scheduled forward in time, ensuring the loads placed on them are within capacity
– The non-bottleneck resources are then scheduled to support the resource
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Comparing SM to JIT
• JIT:– is limited to repetitive manufacturing– requires a stable production level– does not allow very much flexibility in the
products produced – still requires work in process when used with
kanban so that there is "something to pull"
• Vendors need to be located nearby because the system depends on smaller, more frequent deliveries
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Conclusion
• Five steps in the Theory of Constraints– 1. Identify the system constraints– 2. Exploit the system constraints– 3. Subordinate everything to that decision– 4. Elevate the system constraints– 5. If the constraints have been broken, go back
to step 1. Do not let INERTIA take over
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