SMED: The Lean Technique That Can Transform Manufacturing Efficiency

In today's competitive manufacturing environment, companies are constantly searching for ways to increase flexibility, reduce costs, and respond more quickly to customer demand. One of the most powerful Lean Manufacturing techniques for achieving these goals is SMED, which stands for Single-Minute Exchange of Dies.

Despite its name, SMED is not limited to changing dies in a press machine. It is a systematic methodology for reducing setup or changeover times in any manufacturing process. Whether switching between product models, adjusting machine settings, or preparing production lines, SMED helps organizations minimize downtime and maximize productivity.

What is SMED?

SMED was developed in the 1950s and 1960s by Japanese industrial engineer Shigeo Shingo as part of the Toyota Production System. The primary objective is to reduce setup times to less than ten minutes or at least make them dramatically shorter than before.

Long changeovers force manufacturers to produce large batches in order to justify the downtime. While this may seem efficient, it often results in excessive inventory, longer lead times, and reduced flexibility. SMED addresses this challenge by making changeovers so quick that smaller production batches become economically viable.

The SMED methodology follows three main steps:

1. Separate Internal and External Activities

Internal activities can only be performed while the machine is stopped, whereas external activities can be completed while the machine is still running. The first step is to identify each activity and determine whether it truly requires production to stop.

2. Convert Internal Activities into External Ones

Many tasks traditionally performed during downtime can actually be completed beforehand. Preparing tools, preheating equipment, organizing materials, or verifying settings before shutdown significantly reduces idle time.

3. Streamline Remaining Internal Activities

For the tasks that must occur during the changeover, the goal is to simplify and standardize every step. Quick-release fasteners, standardized tooling, parallel operations, and visual work instructions all contribute to faster and more consistent setups.

Reducing setup times delivers benefits that extend far beyond the production floor. Faster changeovers enable manufacturers to produce smaller batches without sacrificing efficiency, leading to lower inventory levels and improved responsiveness to customer demand.

Let´s see a simple example to illustrate this technique.

Imagine a packaging line that requires 90 minutes to switch from one product size to another. By analyzing the setup process, the team discovers that many tools are collected only after the machine stops, settings are adjusted manually, and operators perform tasks sequentially.

After applying SMED principles, tools are prepared in advance, machine settings are standardized, and two operators perform different tasks simultaneously. The result? The changeover time drops from 90 minutes to just 15 minutes. The company can now produce smaller batches, reduce inventory, and respond more quickly to changing customer orders.

SMED is more than a technique for speeding up machine setups, it is a mindset focused on eliminating waste and improving operational agility.

In a world where customer expectations continue to evolve and product lifecycles become shorter, the ability to change production quickly is a significant competitive advantage.

Whether you manage a large manufacturing facility or a small production line, implementing SMED can unlock hidden capacity, improve efficiency, and support a more responsive and resilient supply chain. Sometimes, the biggest improvements come not from working harder, but from making every minute count.

Bottlenecks Theory vs. Theory of Constraints: Are They the Same Thing?

If you’ve spent any time around operations or supply chain teams, you’ve probably heard someone say, “We need to fix the bottleneck.”

And they’re not wrong.

But here’s where things get interesting: fixing a bottleneck isn’t the same thing as applying the Theory of Constraints (TOC) even though the two ideas are closely related.

We have already spoken about Theory of Constraints in this blog:

- Addressing bottlenecks

- Drum-buffer-rope

- The Goal

But it is worth explaining in detail the differences between Bottlenecks Theory and Theory of Constraints, but first: What’s a Bottleneck?

A bottleneck is simply the slowest step in a process, the part that limits how much your system can produce.

Imagine this:

• Production can make 1,000 units per day

• Packaging can only handle 600 units per day

Packaging is the bottleneck. It doesn’t matter how fast production runs, your total output is capped at 600 units.

Bottleneck theory focuses on identifying that slow step and improving it.

You might add labor, reduce downtime, upgrade equipment etc. The goal is to increase flow by fixing the slowest point.

Now: What Is Theory of Constraints (TOC)?

The Theory of Constraints, developed by Eliyahu M. Goldratt, takes this idea much further.

TOC says: Every system has one constraint that determines its overall performance, and here’s the key that constraint isn’t always a machine, it could be a policy, a forecasting method, a batch size rule etc.

TOC isn’t just about finding the slow step. It’s about managing the entire organization around whatever is currently limiting throughput and profit.

For example, imagine you increase manufacturing capacity, but sales can’t sell more product. The constraint was never production. It was demand.

Optimizing production in that case just creates more inventory.

TOC forces you to look at the whole system before investing time and money.
 
Fixing bottlenecks is good operations management, managing constraints is smart business strategy. One improves a step. The other improves the system, and in today’s volatile supply chain environment, systems thinking wins.

 

Digital twin: Conecting the digital and real world

The term “digital twin” might sound futuristic, but it’s quickly becoming a practical tool reshaping how operations and supply chains work today.

In simple terms, a digital twin is a virtual replica of a real-world object, system, or process; anything from a single machine to an entire manufacturing network.

Imagine your factory, warehouse, or supply chain recreated in a digital space. This virtual version mirrors what’s happening in real time, thanks to data flowing in from sensors, IoT devices, and business systems. Every movement, transaction, and temperature change can be captured and reflected in the digital twin.

So, what’s the point? The value lies in simulation and insight. A digital twin allows you to experiment and test scenarios without affecting actual operations. You can explore what might happen if a supplier goes offline, if demand spikes unexpectedly, or if a new route could shorten delivery times. Instead of reacting to problems after they occur, you can anticipate and plan for them.

This technology helps organizations make smarter, faster decisions. Maintenance can become predictive instead of reactive. Inventory planning can adjust automatically to real-time demand. Logistics teams can visualize the entire flow of goods and identify inefficiencies before they cause delays.

Ultimately, a digital twin acts as your operation’s virtual brain, continuously learning, adapting, and optimizing. It bridges the gap between the physical and digital worlds, giving supply chain leaders greater visibility, control, and confidence in every decision.

The future of operations isn’t just physical anymore. It’s mirrored, modeled, and improved through digital twins.

 

Balancing OEE with Other Supply Chain KPIs: Navigating the Tradeoffs

In the world of operations, few metrics get as much attention as Overall Equipment Effectiveness (OEE). OEE measures how effectively a manufacturing asset is utilized by combining three factors: availability (uptime), performance (speed vs. ideal cycle time), and quality (good units produced vs. total units).

In simple terms, it’s a snapshot of how close a machine or line is to running at its theoretical maximum potential. Improving OEE is often seen as a direct path to better productivity and lower costs, but like many metrics, focusing on it in isolation can create conflicts with other critical supply chain goals.

For instance, pushing OEE higher often means striving for longer production runs and fewer changeovers. That’s good for machine efficiency, but it can hurt inventory turns and customer responsiveness. A plant that maximizes OEE by producing large batches of a single SKU may end up tying up working capital in excess stock and reducing the ability to adapt to shifting demand. Similarly, prioritizing OEE can clash with on-time delivery if equipment schedules are optimized for efficiency rather than customer requirements.

Another tradeoff emerges with flexibility and innovation. To keep OEE high, operations teams may resist frequent product launches or engineering changes, both of which introduce downtime, lower yields, and slower cycle times. Yet in today’s market, agility and product variety often matter just as much as asset utilization.

So how do you balance these competing priorities? The key is to treat OEE not as an end in itself, but as one piece of a broader performance puzzle. A mature operations strategy aligns OEE with business objectives by:

• Defining the right horizon: Short-term dips in OEE may be acceptable if they support long-term goals like faster customer response or product diversification.
• Using tiered KPIs: Pair OEE with customer-facing measures such as fill rate, lead time, and service level, ensuring that equipment efficiency doesn’t come at the expense of market performance.
• Driving continuous improvement, not perfection: The pursuit of 100% OEE is unrealistic. Instead, focus on targeted improvements that also strengthen supply chain resilience.

In the end, OEE is a powerful tool for uncovering hidden losses and improving operations, but it should never overshadow the broader mission: delivering the right product, at the right time, at the right cost.

Balancing OEE with other KPIs ensures that efficiency gains translate into true supply chain value.

The Hidden Factory: The Silent Killer of Supply Chain Efficiency

In supply chain operations, we pride ourselves on precision, efficiency, and continuous improvement.

But what if I told you there’s an entire shadow process operating inside your workflows quietly consuming time, resources, and money and it’s not even on your radar?

Welcome to the world of the Hidden Factory.

What is a Hidden Factory?

A Hidden Factory is the collection of all the rework, corrections, and unofficial fixes that happen behind the scenes to make a process appear like it's working smoothly. These aren’t logged as defects. They don’t show up in your dashboards. But they exist.

These might look like:

• Warehouse staff quietly relabeling mis-picked items before shipping.
• Customer service reps manually adjusting inventory levels in the system to correct errors.
• Planners double-checking forecasts with spreadsheets because they don’t trust the MRP output.

Individually, these “workarounds” seem harmless even helpful. But collectively, they signal process gaps that are eating into your margins and scalability.

Hidden factories are dangerous because they create the illusion of control. Everything looks good on paper, but under the surface, people are compensating for broken processes.

The good news is, Hidden factories can be found and fixed. Here are some ways to shine a light on them:

1. Listen to the “Off-the-Record” Conversations; pay attention when someone says:

“Oh, I always fix that before it causes a problem.” “It’s faster if I just do it this way.”

2. Map the Actual Process (Not the SOP)

Use value stream mapping to compare how the process is supposed to work versus how it actually works. You'll often find extra steps that aren't documented anywhere, that's your hidden factory.

3. Look at Cycle Time Variance

If your standard cycle time says an order takes 3 hours, but in practice it’s closer to 5, that discrepancy is usually where the rework is hiding.

4. Involve the Front Lines

Your team knows. Engage operators, planners, and support staff early and often, they live the day-to-day realities that KPIs can’t always capture.

Good Distribution Practices (GDP) & Good Manufacturing Practices (GMP)

 

Good distribution practices (GDP) and good manufacturing practices (GMP) are quality standards and guidelines that have the same objective, to ensure medical device and pharmaceutical products are safe, meet their intended use, and comply with regulations.

GMP focuses on manufacturing processes, while GDP covers distribution activities.

Good manufacturing practices involve consistently producing products that meet quality standards. This requires the implementation of a system where the aim is to minimize risks, from incorrect labelling of products to contamination to incorrect ingredients and everything in between. GMP cover all parts of the production process, from raw materials through to the production of the finished product.

Good distribution practices involve maintaining the quality and integrity of products through all stages of the supply chain. GDP applies to warehousing, storage, and transportation, and it covers everything from storing and transporting products under the right conditions and ensuring product integrity at the correct destination on time.

There are parts of GDP that are unique, so they don’t apply to GMP. Those unique parts of GDP include guidance on transportation covering aspects such as temperature control, vehicle controls, and conducting risk assessments on transport routes.

Logistionary: Kanban

Kanban is a visual scheduling system for lean manufacturing.

It all started in the early 1940s when the first Kanban system was developed by Taiichi Ohno for Toyota automotive in Japan. It was created as a simple planning system, the aim of which was to control and manage work and inventory at every stage of production optimally.

The Kanban method gets its name from the use of kanban, visual signalling mechanisms to control work in progress for intangible work products.

Kanban aligns inventory levels with actual consumption. A signal tells a supplier to produce and deliver a new shipment when a material is consumed. This signal is tracked through the replenishment cycle, bringing visibility to the supplier, consumer, and buyer.

In contexts where supply time is lengthy and demand is difficult to forecast, often the best one can do is to respond quickly to observed demand. This situation is exactly what a kanban system accomplishes, in that it is used as a demand signal that immediately travels through the supply chain.

Kanban cards are a key component of kanban, and they signal the need to move materials within a production facility or to move materials from an outside supplier into the production facility. The kanban card is, in effect, a message that signals a depletion of product, parts, or inventory. When received, the kanban triggers replenishment of that product, part, or inventory.

Three-bin system

An example of a simple kanban system implementation is a "three-bin system" for the supplied parts, where there is no in-house manufacturing. One bin is on the factory floor (the initial demand point), one bin is in the factory store (the inventory control point), and one bin is at the supplier. The bins usually have a removable card containing the product details and other relevant information, the classic kanban card.

When the bin on the factory floor is empty (because the parts in it were used up in a manufacturing process), the empty bin and its kanban card are returned to the factory store (the inventory control point). The factory store replaces the empty bin on the factory floor with the full bin from the factory store, which also contains a kanban card. The factory store sends the empty bin with its kanban card to the supplier. The supplier's full product bin, with its kanban card, is delivered to the factory store; the supplier keeps the empty bin. This is the final step in the process. Thus, the process never runs out of product, and could be described as a closed loop, in that it provides the exact amount required, with only one spare bin so there is never oversupply.

If all this is confusing, and you´re still not clear on how Kanban works, Im sure the next image will make everything fall into place! One image is indeed worth a thousand words as they say!

Addressing a bottleneck with Theory of Constraints

 

The Theory of Constraints is an approach to improving organizational performance; the rationale behind this methodology is that in every organizational system, there is one constraint that limits the output, and only when this constraint is addressed we can improve the whole process.

No matter how much we improve the rest of the non-constrained steps, the process will not improve until we improve the weakest link.

The Theory of Constraints uses five steps for optimising systems, allowing to address constraints is the simplest way possible.

Step 0: define the goal

Each process has a goal, and understanding the goal is often the most difficult step in the process. Finding the right goal and the right metrics to measure progress toward that goal will be critical to your success.

Step 1: Identify the bottleneck

In a similar way, each system has one constraint that determines the throughput of the entire process.

The constraint can be a person, a team, a physical machine, one organizational rule, or anything else that limits the output of a process.  The constraint is often called a bottleneck.

As mentioned earlier, making improvements anywhere but the bottleneck will not improve the throughput of the system and it can even have a negative effect.

To help identify the bottleneck, you can use tools like flow charts, swim lane diagrams, root cause analysis, Pareto charts, or queuing models, but it is critical to define what is the step that is limiting the system.

It’s important to understand that being a bottleneck doesn’t mean a person or team is bad at what they do or that they’re doing anything wrong.  Being the bottleneck is neither good nor bad; it’s just a fact of the system.  There’s always one constraint, and as we will say later on, once that constraint has been addressed, a new one will come up.

Step 2: Exploit the bottleneck

Once we have identified the step that is constrained, the first way to address it is to “exploit” it.

Exploiting the bottleneck means eliminating any work done by the bottleneck that doesn’t contribute towards the throughput.

There are several options when it comes to exploiting a bottleneck:

      -      Make sure the bottleneck works on only one thing at a time.

-      Remove any non-throughput producing work from the bottleneck.

-      Shield the bottleneck from interruptions.

-      Make sure that the bottleneck is never idle or waiting for information, equipment, or materials.

It’s important to only change one thing at a time as if multiple changes are made it will be impossible to tell what change had the positive effect.

After each change, it’s important to go back to the beginning to make sure the bottleneck hasn’t changed to a point where it is no longer the constraint.

Step 3: Subordinate Decisions to the Bottleneck

After you’ve exhausted what you can do through exploiting the bottleneck, the next step is to subordinate decisions to the bottleneck. Subordinating decisions means the rest of the system works to help the bottleneck produce maximum value.

In a constrained system, anyone working beyond the pace of the bottleneck is not increasing the throughput of the system, therefore instead of working faster, it’s more productive to work to the pace of the bottleneck and use the extra capacity to support the bottleneck further.

As with the exploit step, measure the result and go back to the beginning. 

Step 4: Elevate the bottleneck

After doing what you can to exploit and subordinate, you can elevate the performance of the bottleneck.

Elevating the bottleneck requires time and money, so it’s done only after exploiting and subordinating.

Some of the below examples can help elevate the bottleneck and improve performance:

 

-       Get more people that can do the same work as the bottleneck.

-       Buy more or faster machines.

-       Give people training and better tools.

-       Coach for individual improvement.

-       Improve the workspace.

-       Change organisational policies.

Often, we jump right directly to elevating by adding people, getting training, buying equipment and tools.  These changes can be expensive, and it takes time to get a positive impact on throughput.  They could even have a negative effect in the short term.

Elevate as a last resort when you can’t find any more ways to exploit or subordinate.

Step 5: Repeat

Every time you find a potential improvement, implement it, measure the results, and go back to the beginning.  Make sure the goal is still valid and see if the constraint has moved.

COVID-19: impacts on supply and demand

How resilient and responsive is your supply chain? If you did not know before, there’s a chance you will soon find out.

There’s been a lot of talk about risk management with regards to Brexit, which seemed like enough of a challenge, but now many nations around the world are facing an event that, unlike Brexit, couldn’t be predicted or properly planned for.  

As supply chains tend to be highly customer-focused, changes in customer behaviour and demand has impacts throughout the supply chain.

In China, retailers reported changes to the demand profiles of specific products, as shopper behaviour changed in response to the outbreak of COVID-19.

One trend observed since the outbreak has been a surge in online shopping. This is not surprising and a consequence of people going out less, in response to government advice to self-isolate.

KFC and Pizza Hut started trialling contactless delivery services in an attempt to reduce person-to-person transmission and JD.com introduced five vending machines to a residential compound in Beijing, offering residents 24/7 access to fresh fruit, vegetables and more. 

Demand and supply planning becomes difficult when demand patterns change.  In the case of COVID-19, there isn’t a sufficiently comparable historical event that can be used to get a sense for customer demand.  For products that are seeing surges in demand as a result of the outbreak, supply chains will likely struggle with replenishment and lead times will increase, unless additional sources can be found and/or capacity can be increased at current suppliers. This will affect on-shelf availability (OSA).

Some retailers have attempted to actively manage demand for products that shoppers seem to be stockpiling.  UK retailer Boots has tried to reduce the demand for hand sanitizers by introducing signs on the shelves that limit customers to two per shopper.  In Australia, Woolworths has applied a quantity limit of four packs of toilet paper per purchaser.

Retailers should consider the possibility of a scenario in which consumers go out less and demand more grocery home deliveries.  If this happens, retailers may need to enhance online delivery capacity in order to meet increased online demand. 

Finally, businesses need to understand where their supply network partners are located and consider what the impact of the virus is in each of those locations.  They should also consider how worsening circumstances might affect operations at these locations.  Businesses will need to assess whether they can reduce risk by procuring finished goods and raw materials from alternative sources.  

Situation is changing rapidly and every day we have new news, but ultimately the reality is that supply chains will be severely impacted, but will also be a key player in solving the crisis that is yet to fully materialise across the globe.

Zero waste - the Unilever journey

Waste minimization is the process of reducing the amount of waste produced with the aim to eliminate the generation of harmful and persistent wasters. Waste minimization involves efforts to minimize resources and energy use during manufacture.

Waste management on the other hand, focuses on processing waste after it´s created, concentrating on reducing, reusing and recycling products and components. Waste minimization should be seen as a primary focus for most waste management strategies.

Zero waste is a philosophy that encourages the redesign of resource life cycles so that all products are reused and no waste is generated, it encompasses more than eliminatig waste through recycling and reuse, it focuses on restructuring the production and distribution systems to reduce waste.

Many companies have set ambitious targets waste reduction, and factories have been targeted as the primarily function to trial waste reduction principles.

One prime example of this journey to zero waste is Uniliver; the giant FMCG started his journey back in 2009 with the aim to achieve zero waste across their global factory network by 2020. They achieved this target in 2014, 6 years ahead of plan. Here is how they did it:

The challenge is now to roll out these best practices from factories to distribution centres, head offices and customers. Hopefully one day, the zero waste philosophy will be part of everybody´s life, in the meantime, a few pioneers are showing us the way. Only a few changes in our day to day life will mean a start to a journey to reduce our impact in our planet.

http://www.trashisfortossers.com/