Goldratt’ s Rules of Production Scheduling
Do not balance capacity balance the flow
The level of utilization of a nonbottleneck resource is not determined by its own potential but by some other constraint in the system
Utilization and activation of a resource are not the same
An hour lost at a bottleneck is an hour lost for the entire system
An hour saved at a nonbottleneck is a mirage
Goldratt’ s Rules of Production Scheduling (Continued)
Bottlenecks govern both throughput and inventory in the system
Transfer batch may not and many times should not be equal to the process batch
A process batch should be variable both along its route and in time
Priorities can be set only by examining the system’ s constraints and lead time is a derivative of the schedule
Goldratt’ s Theory of Constraints (TOC)
Identify the system constraints
Decide how to exploit the system constraints
Subordinate everything else to that decision
Elevate the system constraints
If, in the previous steps, the constraints have been broken, go back to Step 1, but do not let inertia become the system constraint
Goldratt’ s Goal of the Firm
Performance Measurement: Financial
Net profit
an absolute measurement in dollars
Return on investment
a relative measure based on investment
Cash flow
a survival measurement
Performance Measurement: Operational
1. Throughput
the rate at which money is generated by the system through sales
2. Inventory
all the money that the system has invested in purchasing things it intends to sell
3. Operating expenses
all the money that the system spends to turn inventory into throughput
Productivity
Does not guarantee profitability
Has throughput increased?
Has inventory decreased?
Have operational expenses decreased?
Unbalanced Capacity
Earlier we discussed balancing assembly lines
The goal was a constant cycle time across all stations

Synchronous manufacturing views constant workstation capacity as a bad decision
Capacity Related Terminology
Capacity is the available time for production
Bottleneck is what happens if capacity is less than demand placed on resource
Nonbottleneck is what happens when capacity is greater than demand placed on resource
Capacity-constrained resource (CCR) is a resource where the capacity is close to demand placed on the resource
Time Components of Production Cycle
Setup time is the time that a part spends waiting for a resource to be set up to work on this same part
Process time is the time that the part is being processed
Queue time is the time that a part waits for a resource while the resource is busy with something else
Time Components of Production Cycle (Continued)
Wait time is the time that a part waits not for a resource but for another part so that they can be assembled together

Idle time is the unused time that represents the cycle time less the sum of the setup time, processing time, queue time, and wait time
Saving Time
Drum, Buffer, Rope

Performance Measurement Financial
Net profit
an absolute measurement in dollars
Return on investment
a relative measure based on investment
Cash flow
a survival measurement
Performance Measurement Operational
1. Throughput
the rate at which money is generated by the system through sales
2. Inventory
all the money that the system has invested in purchasing things it intends to sell
3. Operating expenses
all the money that the system spends to turn inventory into throughput
Productivity
Does not guarantee profitability
Has throughput increased?
Has inventory decreased?
Have operational expenses decreased?
Some Capacity Related Terminology
Capacity
Available time for production
Bottleneck
Capacity is less than demand placed on resource
Nonbottleneck
Capacity is greater than demand placed on resource
Capacity-constrained resource (CCR)
Capacity is close to demand placed on resource
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
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
Saving Time
Drum, Buffer, Rope
Case: Kristen’ s Cookies

Introduction to Drum Buffer Rope (DBR)
?What is Drum Buffer Rope?
Drum Buffer Rope (DBR) is a planning and scheduling solution derived from the Theory of Constraints (ToC).
The fundamental assumption of DBR is that within any plant there is one or a limited number of scarce resources which control the overall output of that plant. This is the “drum”, which sets the pace for all other resources.
In order to maximize the output of the system, planning and execution behaviors are focused on exploiting the drum, protecting it against disruption through the use of “time buffers”, and synchronizing or subordinating all other resources and decisions to the activity of the drum through a mechanism that is akin to a “rope”.
Theory of Constraints
ToC (Theory of Constraints), also called Constraint Management, is a philosophy and set of techniques used to manage an organization. Most widely implemented in manufacturing operations, it teaches management how to identify and direct their focus on the few critical drivers that matter to the bottom line performance.
Eliyahu Goldratt originated the idea in his book The Goal as a way of managing the business to increase profits. ToC is a proven method that can be used by existing personnel to increase throughput (sales), reliability, and quality while decreasing inventory, WIP, late deliveries, and overtime. Successful organizations also adopt ToC to help make tactical & strategic decisions for continuous improvement.
The crucial insight of ToC is that only a few elements (constraints) in a business control the financial results of the entire company. ToC tools identify these constraints, and focus the entire organization on simple, effective solutions to problems that seemed insurmountably complex and unsolvable.
The Scheduling Problem
When one looks at the load versus capacity, one must look at each resource individually. The aggregate view of, for example, 1000 hours available in the factory versus 880 hours of demand doesn’t adequately describe the situation. In figure 1, we see that most work
centers have extra capacity, while work center 3 is fully loaded and cannot accept more work. The true state of this plant is that it is full and cannot accept more work that involves WC3.
?© 2004-2008 Mark Woeppel pinnacle-strategies.com Page 1
?
Demand
Capacity
Introduction to Drum Buffer Rope (DBR)
??????????WC4 WC3 WC2 WC1
???In addition, we must consider the time frame in which the demand occurs. A monthly or weekly aggregate view of demand may not be sufficient to take action and deliver work on time.
Demand: What is needed?
Capacity: What is available?
??900 800 700 600 500 400 300 200 100
0
???????????????????D1 D2 D3 D4 D5
To solve this problem, most systems will offset by some standard fixed lead time, but all that does is move the peak over. Forward scheduling algorithms will not “see” the peak until it’s too late
The peak demand must be moved to open capacity.
If you ignore peak demands, you will have expediting, overtime, additional WIP, late deliveries because capacity may not be available when needed. This will have negative effect on system throughput, due date performance, and lead times.
ToC in Production
The Theory of Constraints is an integrated management philosophy and set of techniques which serve to manage & optimize the activity of the business.
ToC begins with one underlying assumption; the performance of the system’s constraint will determine the performance of the entire system. To help you understand explain, we use a chain as an analogy. The strength of the chain is determined by its weakest link. What determines the strength of the chain? Its weakest link.
© 2004-2008 Mark Woeppel pinnacle-strategies.com Page 2
?2500
2000
1500
1000
500
0
Minutes
Demand
Capacity
Introduction to Drum Buffer Rope (DBR)
??The process of delivering a product or service is very much like a chain; each resource and function are linked. It only takes one element in the system to fail, to cause the entire system to fail.
In order to improve the system, we must optimize the weakest link; the constraint or drum. All other resources are subordinated to that. In scheduling terms, we
1. Developadetailedscheduleforthedrumresource
2. Add buffers to protect the performance of that resource
3. Synchronizethescheduleofallotherresourcestothedrumschedule
The Drum Buffer Rope Solution
Identify the system’s constraint
The first step is to identify the drum. The drum is typically the most heavily loaded resource (or workcenter) in the plant.
????????WC4 WC3 WC2 WC1
???© 2004-2008 Mark Woeppel
pinnacle-strategies.com
Page 3
?2500
2000
1500
1000
500
0
Introduction to Drum Buffer Rope (DBR)
?Exploit the constraint
Demand: What is needed?
Capacity: What is available?
??900
800
700
600
500
400
300
200
100
0
????40 hrs / week
P1 demand 51 on day 5 50 on day 3
P2 demand
10 on days 1-5
?????????????????The Drum Schedule DAY PART QTY MIN
1 P2 10 240 1 P2 10 240 2 P2 10 240 2 P1 20 240 3 P1 30 360 3 P2 5 120 4 P2 15 360 5 P1 40 480 6 P1 11 132
The impact on the non-constraints is to smooth out the load, because their processes are connected to the constraint resource.
600 500 400 300 200 100
0
D1 D2 D3 D4 D5
D1 D2 D3 D4 D5
Once the drum has been identified, a detailed schedule is prepared to satisfy the customer requirements, resolving the peak loads.
??????????P2
P1
P2
P2
P1
??P1
P2
??P2
P2
?P1
????????????????WC1 WC3
??© 2004-2008 Mark Woeppel
pinnacle-strategies.com
Page 4
?Minutes
Introduction to Drum Buffer Rope (DBR)
?The Buffer
The buffer is a period of time to protect the drum resource from problems that occur upstream from the drum operation. Its effect to provide a resynchronization of the work as it flows through the plant.
The buffer compensates for process variation, and
makes DBR schedules very stable, immune to most
problems. It has the additional effect of eliminating the need for 100% accurate data for scheduling. It allows the user to produce a “good enough” schedule that will generate superior results over almost every other scheduling method.
Since the buffer aggregates variation, it also allows to operate the plant with much lower levels of work in process, producing dramatic reductions in production lead times and generating a lot of cash that was tied up on inventory.
The “extra” capacity at the non-constraints helps, too. Since the plant is not overloaded with work it cannot do, the resources can “catch up” when problems strike, without affecting the drum or global throughput.
Synchronize to the Drum – Subordination
After the drum has been scheduled, material release and shipping are connected to it, using the buffer offset. Material is released at the same rate as the drum can consume it. Orders are shipped at the rate of drum production.
DBR Scheduling Algorithm
The process of scheduling the factory first focuses on the primary objective of the facility, to ship to committed delivery date. Thus we first find the due date of the order, and add a shipping buffer to create an “ideal” finish date with confidence.
?????????© 2004-2008 Mark Woeppel pinnacle-strategies.com Page 5
?
Introduction to Drum Buffer Rope (DBR)
?From this planned finish date, the order is backward scheduled to identify an “ideal” time to work on the drum resource, a “latest due by” (LBD) date.
All orders are scheduled to fit on the drum using two passes; first, by assigning all batches an ideal placement on the drum schedule.
When the batch does not fit, i.e., there is another occupying its space, the batch is scheduled earlier in time so the order due date is not violated. This may result in some jobs starting before today, and not all jobs may be ready to start at the drum resource.
The drum is then forward scheduled to resolve these conflicts, and potentially late jobs are identified (the red batch).
???© 2004-2008 Mark Woeppel pinnacle-strategies.com Page 6
?
Introduction to Drum Buffer Rope (DBR)
??After the drum is schedule, the operations after the drum are scheduled forward in time from the drum completion date.
?Then, the jobs feeding the drum are backward scheduled from the start of the resource buffer .
© 2004-2008 Mark Woeppel pinnacle-strategies.com Page 7
?
Introduction to Drum Buffer Rope (DBR)
??© 2004-2008 Mark Woeppel pinnacle-strategies.com Page 8
?

Outline
Outline -Continued
Outline -Continued
Outline -Continued
Learning Objectives
When you complete this chapter you should be able to:
Learning Objectives
When you complete this chapter you should be able to:
Delta Airlines
Strategic Importance of Short-Term Scheduling
Scheduling Issues
Scheduling Decisions
Scheduling Flow
Forward and Backward Scheduling
Forward and Backward Scheduling
Forward and Backward Scheduling
Different Processes/ Different Approaches
Scheduling Criteria
Scheduling Process-Focused Facilities
Planning and Control Files
Loading Jobs
Input-Output Control
Input-Output Control Example
Input-Output Control Example
Input-Output Control Example
Gantt Charts
Gantt Load Chart Example
Gantt Schedule Chart Example
Assignment Method
Assignment Method
Assignment Method
Assignment Method
Assignment Example
Assignment Example
Assignment Example
Assignment Example
Sequencing Jobs
Sequencing Example
Sequencing Example
Sequencing Example
Sequencing Example
Sequencing Example
Sequencing Example
Sequencing Example
Sequencing Example
Sequencing Example
Sequencing Example
Comparison of Sequencing Rules
Critical Ratio (CR)
Critical Ratio Example
Critical Ratio Technique
Sequencing N Jobs on Two Machines: Johnson’ s Rule
Johnson’ s Rule
Johnson’ s Rule Example
Johnson’ s Rule Example
Johnson’ s Rule Example
Johnson’ s Rule Example
Limitations of Rule-Based Dispatching Systems
Finite Capacity Scheduling
Finite Capacity Scheduling
Finite Capacity Scheduling
Theory of Constraints
Bottlenecks
Drum, Buffer, Rope
Scheduling Repetitive Facilities
Scheduling Repetitive Facilities
Scheduling Services
Scheduling Services
Scheduling Services
Demand Management
Scheduling Service Employees With Cyclical Scheduling
Cyclical Scheduling Example
Cyclical Scheduling Example
Cyclical Scheduling Example
Cyclical Scheduling Example
Cyclical Scheduling Example
Cyclical Scheduling Example
Cyclical Scheduling Example
Cyclical Scheduling Example
Cyclical Scheduling Example

Goldratt’ s Goal of the Firm
Performance Measurement: Financial
Net profit
an absolute measurement in dollars
Return on investment
a relative measure based on investment
Cash flow
a survival measurement
Performance Measurement: Operational
1. Throughput
the rate at which money is generated by the system through sales
2. Inventory
all the money that the system has invested in purchasing things it intends to sell
3. Operating expenses
all the money that the system spends to turn inventory into throughput
Productivity
Does not guarantee profitability
Has throughput increased?
Has inventory decreased?
Have operational expenses decreased?
Unbalanced Capacity

Synchronous manufacturing views constant workstation capacity as a bad decision
The Statistics of Dependent Events
Rather than balancing capacities, the flow of product through the system should be balanced
Capacity Related Terminology
What is a Constraint?
Any factor that limits system performance and restricts its output.

Capacity is the available time for production
Bottleneck is what happens if capacity is less than demand placed on resource
Nonbottleneck is what happens when capacity is greater than demand placed on resource
Capacity-constrained resource (CCR) is a resource where the capacity is close to demand placed on the resource
Saving Time
Drum, Buffer, Rope
Batch Sizes
What is the batch size?

One?
Infinity?
Theory of Constraints (TOC)
Short-Term Capacity Planning
Theory of Constraints
Identification and management of bottlenecks
Product Mix Decisions using bottlenecks
Long-term Capacity Planning

Economies and Diseconomies of Scale
Capacity Timing and Sizing Strategies
Systematic Approach to Capacity Decisions
7 Key Principles of TOC
The focus is on balancing flow, not on balancing capacity.

Maximizing output and efficiency of every resource will not maximize the throughput of the entire system.

An hour lost at a bottleneck or constrained resource is an hour lost for the whole system.
An hour saved at a non-constrained resource does not necessarily make the whole system more productive.
7 Key Principles of TOC
Inventory is needed only in front of the bottlenecks to prevent them from sitting idle, and in front of assembly and shipping points to protect customer schedules. Building inventories elsewhere should be avoided.
Work should be released into the system only as frequently as the bottlenecks need it. Bottleneck flows should be equal to the market demand. Pacing everything to the slowest resource minimizes inventory and operating expenses.
7 Key Principles of TOC
Application of TOC
Identify The System Bottleneck(s).
Exploit The Bottleneck(s).
Subordinate All Other Decisions to Step 2
Elevate The Bottleneck(s).
Do Not Let Inertia Set In.
Bal Seal Engineering Managerial Practice 7.1
Bal Seal had problems with excessive inventory, long lead times and long work hours.
They were operating above capacity but on-time shipment rate was 80-85%
Bal Seal implemented TOC with dramatic and almost immediate results.
Excessive inventory dried up
Extra capacity was experienced everywhere but at the constraint
Total production increased over 50%
Customer response time decreased from 6 weeks to 8 days
On-time shipments went up to 97%
Identification and Management of Bottlenecks
A Bottleneck is the process or step which has the lowest capacity and longest throughput.

Throughput Time is the total time from the start to the finish of a process.

Bottlenecks can be internal or external to a firm.

Where is the Bottleneck? Example 7.1
Comparing Synchronous Manufacturing to JIT
JIT is limited to repetitive manufacturing
JIT requires a stable production level
JIT does not allow very much flexibility in the products produced
Comparing Synchronous Manufacturing to JIT (Continued)
JIT 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