Posts Tagged ‘Drum Buffer Rope’

dbrAs a recent article in APICS Magazine points out, “while containing an issue and eliminating an issue are different things, containment does help keep the problem from getting worse.”

And that pretty well sums up the simple concept behind the long-touted Drum-Buffer-Rope (or DBR) theory first espoused by Dr. Eliyahu Goldratt many years ago, and brought most notably and literally to life in his best-selling book, The Goal.

DBR, as APICS points out, has held its own for a good while now as a method for scheduling and managing operations that have internal constraints or a capacity-constrained resource.  That constrained resource with the least capacity will always set the pace for the entire production line.  Thus, providing it with a “buffer” of inventory is the simplest way to prevent starving that constraint and thus creating a full stoppage due to lack of work.  Simply put, make sure your “constraint” has plenty of inventory in front of it and you have effectively eliminated it as your worst constraint.

From there, the Theory of Constraints tells us, one moves on to the next most critical constraint… and so on, gradually working one’s way through a cascading series of constraints in the never-ending search for continuous improvement.

The idea of DBR then is to put a single information link – the “rope” – between the constraint and production starts.  Because it’s a single link, a DBR production control system becomes simpler even than kanban, which requires communication across many workstations, whether that takes the form of production cards, empty containers or empty spaces for inbound materials.

Of course, variations in processing and material transfer can dash the best of plans.  Here again, DBR can help.  As APICS points out (in an article by William Levinson titled “Completing the Link, Mar/Apr ’15 issue) “If no containment action is taken, inventory accumulates the same way.”  The author gives the example of a traffic jam in a highway operating near capacity when a driver slows down.  Everyone has to slow down, and no one can make up the resulting loss.

Likewise, in a “balanced factory” where each workstation has the same capacity, variation can cause inventory to accumulate and reduce throughput to less than the expected rate, and time lost at any work station theoretically can never be made up.

If all workstations but one (the “constraint”) have excess capacity, “then the problem is limited to that one workstation.  It therefore is necessary to keep a buffer of protective inventory to shield that workstation from starvation.”

The size of that buffer depends on the variation in the system prior to the constraint, notes Levinson.  So while this form of containment may not be a genuine solution, it does eliminate the effect of most of the variation.  Simple, but effective.


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We noted in our prior post an article by Eliyahu Goldratt, author, consultant and father of the Theory of Constraints of production flow, the example of Hitachi Tool Engineering’s challenge to improve workflow while reducing inventory – the Holy Grail of most production facilities.

What, to us at least, makes the Hitachi tale valuable is the fact that their environment features substantial production but in a highly variable product environment – in other words, the same circumstances shared by many of our clients!

Goldratt uses the Hitachi example to show how his noted Drum-Buffer-Rope concepts can be used in practice, not just in theory to better manage workflows.  (For a full copy of his 22 page article, please contact us directly, or leave a comment.)  To recap, however briefly…

Goldratt points out that Hitachi was “unsuccessful” in implementing lean, largely due to sporadic item demand (a highly variable product mix) coupled with a complete changeover in product families every six months.

So, about ten years ago, Hitachi began using the DBR concept in just one plant in Japan.  They ended up improving due-date performance significantly, according to Goldratt, while cutting WIP and lead-times in half, and shipping 20% more product with the same labor force.  Other supply chain improvements and benefits followed, as detailed in the article, including the fact that reduced lead times and better responsiveness on Hitachi’s part led to improved cash flow (freed up cash) for Hitachi’s key distributors, who were then of course anxious to increase business with them.

In effect, Hitachi used DBR to “expose excess capacity” — and to deal with it, Hitachi encouraged its sales force to take advantage of its newly improved throughput performance to actually gain more sales.  And they did — due, of course, to improved deliverability and due-date performance.

Utilizing the TOC concepts of Drum-Buffer-Rope (DBR) Hitachi addressed the issue head on.  The “bottleneck” became the ‘drum beat’ for more orders.  The ‘time-buffer’ translated due-dates into release-dates, and the action of choking (or restraining) the release became the ‘rope’ that tied the order to the release of work.  In fact, it’s how the time-based application of the Theory of Constraints became known as the drum-buffer-rope system.

Many of Goldratt’s conclusions highlight the importance of improving coordination between sales and production – that is, making the production capacities known and clearly communicated, and then coordinating with Sales to optimize the sales-to-production flow, and to let customers know about their improved delivery capabilities and thus take sales from competitors.  (Sales & Operations Planning is a world of topics unto itself, of course.)

The same principles apply today, especially in similarly variable production environments.  A little small-scale experimentation with your bottlenecks, inventory timing, and appropriate constraining at a “bottleneck” work center can be a very good place to start.


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In 2008, well known business consultant, author (of the best-selling book “The Goal” among many others) and ‘founding father’ of the Theory of Constraints, Eliyahu Goldratt, penned a rather lengthy (20 page) article entitled “Standing on the Shoulders of Giants.”  My friend Dr. Donn Novotny recently passed along a copy of the article, which I thought might prove instructive to those in manufacturing with an interest in Lean, TOC and logistics and process improvement.

If you’re interested in a full copy, send me a note or comment in this blog. 

Any improvement in production flow usually comes down in one form or another to flow control – that is, the idea that by increasing or decreasing supply of material (or space, or time) to a work center and managing the resulting buffers, one can optimize the rate of production while minimizing the cost of inventory required to meet that flow.  The results can include faster throughput, better due-date delivery, and lowered expenses.  On this basis, Goldratt’s article supplies some background on the evolution, theory and more importantly, the effective practice of these “lean” techniques.  I’ll take the liberty of synopsizing here…

Roughly, the prevailing school of thought that is generally lumped into the category of “lean” is built on three primary foundations:

1. Henry Ford, and Ford Motor Co., which in the early part of the 20th century solved production dilemmas found in high volume production facilities with little variety or variability.  Essentially, Ford espoused limiting space between work centers (when that space is full, stop production!), and improve the work center after this position, because that is the current bottleneck.  The controlling concept was space reduction and this was often known simply as in-line production.

2. Next came Taiichi Ohno, and Toyota Motors, during the mid to latter 20th century.  Where Ford limited space between work centers, Ohno proposed limiting inventory between centers as well as in the material supply chain.  This led to the term ‘just-in-time’.  When maximum allowed inventory accumulated anywhere in the line, stop production!  These principles worked best for Toyota’s high volume, but “medium” variety environment – one that was often a “stable” environment as well.  (With Toyota, some limited variability in model production was allowed.)  Like Ford, Ohno sought to improve the work center directly after the point where inventory (or in Ford’s case, space) was accumulating, as this pointed to the current bottleneck.  In this environment, Kanban came to exist, and the terms “lean” and TPS (Toyota Production System) came into play.

3. And then, in the 1980s and later, MRP (Material Requirements Planning) and the theories of Eli Goldratt (among others) took the matter to the world of low-volume / high-variety (or unstable) production.  Where Ford limited space and Ohno limited inventory between work centers, Goldratt proposed to limit time between them.  The current bottlenecks would then be those with the most material waiting in front of them – basically, a step up on the shoulders of Ohno, and before him, Ford.  MRP and TOC were the results of this evolution in the process of production. 

Each major theory built on the one before it, at last finishing with Goldratt’s Drum-Buffer-Rope concepts, as described in his seminal work, The Goal. 

Goldratt’s full article explores in more depth than here the implications of the third generation, and the challenges between theory and practice in production centers where variety runs high.  We’ll look at how that worked for one well known manufacturer,Hitachi, in our next post.  Stay tuned…


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In the first of this seven part series of thoughts on manufacturing constraints and scheduling, I started with a reference to Eli Goldratt’s The Goal.  Along the way, we placed links to various online sources for more information.  Obviously, the trove of information is deep.  You really should check them out.

In our own consulting practice, usually we find clients simply want some guidance.  And usually, we provide it ourselves.  Sometimes, we refer them to others with a reputation for solving problems. 

For Lean Manufacturing matters, we like to go to our guys Larry Lukasik and Jim Therrien.  They don’t have a website – they’re too busy doing good work helping companies go lean – but we happily connect them with clients with a need in this area. 

Other times, we’ve called in our good friend Dr. Donn Novotny (referred to earlier as the role model for Alex Rogo in The Goal).  Donn’s President of The Goal Institute, and is a master at solving complex problems with logical thinking processes.  He’s a master teacher of TOC and has worked with companies large and small, all over the world.

Frequently, we apply our Business Process Analysis, a modestly priced fixed-fee engagement whereby we help clients identify and resolve their own bottlenecks, constraints and process gaps.  Once identified, we’ve had great success in solving problems with better processes and, of course, software and technology. 

That technology slant seems to be the field-leveler these days.  The clients we have that are really committed to their tech investments gain real strategic competitive advantage – and most importantly, growth, compared to those with fear of the terrain, or whose commitment to real improvement often just doesn’t compare.

The global landscape is changing, faster than most recognize.  The Internet and its associated Widgets of Productivity are changing the landscape for all of us.  You embrace it, exploit it for your own purposes, or get run over by it.

In this series on Drum-Buffer-Rope thinking, I hope we’ve provided a little food for thought.  This stuff has been around for awhile.  And we’ve barely scratched the surface.  Most of it is about logical thinking processes — but necessary ones, at least in today’s manufacturing environment. 

At the least, I hope we’ve induced you to think about your own constraints, and what you can do about them. 

In solving these kinds of problems on a daily basis, our team gets to see a lot of the best (and sometimes, the worst) practices in action.  The common thread among the best of them is smart people leading smart teams operating under the assumption that, really, what other choice do we have?  Adapt and survive.  Else, not.

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To properly manage an acceptable production flow, relative to the demands of your customer (and in pursuit of on-time, on-budget), a set of rules derived from our previous post’s key points can be established, based on Theory of Constraints logic.  These points are intended to drive the logic of your MRP.  You can find them here, and they are summarized below:

1. Establish the due date requirements for the orders or demand. This provides the first and “ideal” drum to work to.

 2. Identify the CCRs (Capacity Constraint Resources) in the system.

 3. Develop a Drum or a schedule for the CCRs which makes best use of them and is in-line with the needs of the market. The drum is effectively the master production schedule which establishes the “drum beat” and control for the entire system.

 4. Protect the throughput of the factory from statistical fluctuations through the use of time buffers at critical locations. Time buffers are strategically located to protect the throughput of the entire system and to protect the due dates promised to customers.

 5. Use logistical ropes tied to the CCR drum schedules for each resource. The ropes synchronize all non CCRs to generate the timely release of the right materials into the system at the right time. Ropes ensure that operations upstream of CCRs are time phased to CCR requirements and operations downstream do not subsequently impede product flow.

In your overall scheduling, you should insert buffers along the way to protect the constraints from disruptions, expected or otherwise.  Your schedule (The Rope) releases material into your system on a timely basis, tied to the size of these buffers, in order to increase the likelihood of smooth, continuous flow.

A schedule, which above all is intended to be do-able and realistic, is only as good as the team’s ability to manage it, to make it happen.  Focusing on constraints and the correct imposition of buffers (in the right place and size) will help improve the success of your schedule, especially when Murphy raises his head, as invariably happens.  And to come full circle, by managing the critical resource constraints with good scheduling and appropriate systemic buffers, new smaller constraints may begin to appear.  At that point, you go back to step one, identifying and attacking the new constraints – in the ultimate process of continuous improvement.

Next up, some final thoughts…

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We looked earlier at identifying constraints, noting that it is fairly intuitive to observe that the constraint by definition is the weak link in the system.  How do we improve the throughput at the constraint without unduly increasing the expense or cost of doing so?

The answer lies in finite scheduling – The Rope, of Drum-Buffer-Rope thinking – in order to balance the flow (throughput) of our system.  The idea is to control the flow of production through the plant in order to meet sales (market) demand, with the least amount of manufacturing lead time, expense and inventory costs.

Modern MRP software can handle this for you.  In our experience over the years, we’ve seen many manufacturers with a high level of urgency regarding Scheduling.  Often, it’s the first thing they look at when evaluating an MRP system, but the last thing they implement – and for good reason.  Truly tight scheduling simply asks so much of the operators and managers.  We often guide clients to a rough-cut or gross requirements scheduling solution: it’s more important to get the order right, than schedule the shop down to the gnat’s behind – especially since attempts to do so are rarely successful.

All that being said however, The Theory of Constraints (TOC) school of thought, first introduced in Goldratt’s The Goal focuses on five steps to implementing an effective scheduled throughput, which I quote verbatim below.  For a fine (if lengthy) overview go here.

1. Identify the system’s constraint(s).
2. Decide how to exploit the system’s constraint(s).
3. Subordinate everything else to the above decisions.
4. Elevate the system’s constraint(s).
5. If, in the previous steps, a constraint has been broken, return to step one, but do not allow inertia to cause a system’s constraint.

The Rope provides for proper release to the manufacturing flow process, or as put by others, it aids in subordinating all else to the system’s constraint(s).  It’s your schedule.

Broadly speaking, you start by identifying all constraints within the system.  Make these the focus of your attention.  From these, derive your planning, scheduling and control of resources.  Once you’ve identified your capacity constraint resources (your CCRs, or your bottlenecks), schedule orders through them according to the capacity of the resource and market demand (your due date requirements). 

This schedule (or Rope), in effect is a looping-back to the Drumbeat of your demand. 

Next article, a little more info on Scheduling…

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Picking up from our prior post on Throughput…

To get an ideal flow time for a complex assembly, use the version of Little’s Law that stipulates (stay with me here): Flow Time = Inventory / Throughput

To estimate a flow time for an assembly process then, we measure the Inventory (in dollars) across the line or process, measure Throughput in terms of COGS (Cost of Goods Sold) and find their ratio.  This will provide a usable measure of Flow Time.

Same goes for WIP.  Little’s Law implies: Flow Time = WIP / Throughput.  If you reduce WIP, you may reduce your cycle time, but that’s a slippery slope.  If you reduce WIP without making other changes to the variables in the system, you’ll reduce your throughput, eventually affecting lead times and ability to deliver.  You can’t just reduce WIP to get lean.  You need what’s called a variability reduction to maintain or improve throughput with less WIP.

The ideal production scenario, then, is one that can be scheduled with a clear eye on the rhythm of product (the Drum) while cognizant of the cost effects of the Throughput component – setting up the ideal length of time, based on the right amount of inventory — for parts to reach the constrained area (the Buffer)

Next up, the Rope…

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