Balance Batched SMED JIT

BALANCE OF INVENTORY, BATCHES, SMED, JIT, KANBAN

Mike Dixon, PhD

While our previous reading explored why companies hold inventory, this reading focuses on how modern operations management techniques can help reduce unnecessary inventory while maintaining operational effectiveness. Many traditional approaches to manufacturing and operations assumed that large batch sizes and significant inventory levels were a necessary evil of doing business. However, developments in operational efficiency, particularly from Japanese manufacturing techniques, have shown that it’s possible to dramatically reduce inventory levels while improving service and quality.

The Challenge of Balancing Inventory Levels

Companies face a constant tension between having enough inventory to operate efficiently and maintain customer service levels, while avoiding excess inventory that ties up capital and creates waste. This balance is particularly challenging because of several factors:

• Traditional batch production methods that seem to require large runs
• Setup times that make small batches appear inefficient
• The apparent trade-off between efficiency and flexibility
• Fear of stockouts and lost sales
• Complex supply chains with variable lead times

However, techniques like Single Minute Exchange of Dies (SMED) and Just-in-Time (JIT)production have shown that many of these traditional constraints can be overcome throughsystematic process improvement. This reading will explore these methods and how they contribute to more efficient inventory management.

Setup Time and Its Influence on Batch Sizes

Setup time, also known as changeover time, refers to the time required to prepare a machine, production line, or process to switch from producing one product type to another. This includes activities such as:

• Cleaning equipment
• Changing tools or dies
• Adjusting settings
• Running quality checks
• Initial calibration
• Documentation
• Preparing for the next customer or group of customers

For example, in a printing operation, setup time includes cleaning the press, changing plates, loading new paper, adjusting ink levels, and running test prints until quality standards are met.

Why Long Setup Times Lead to Larger Batches

Traditional manufacturing logic suggests that longer setup times make smaller batch sizes economically impractical. This is the fundamental premise behind the concept of economies of scale. Here’s why:

1. Setup Cost Amortization

• Each setup incurs fixed costs (labor, materials, lost production time)
• These costs must be spread across all units in the batch
• Larger batches reduce the per-unit setup cost
• Example: If setup takes 2 hours:
  • Running 100 units = 1.2 minutes of setup time per unit
  • Running 1000 units = 0.12 minutes of setup time per unit

2. Production Economics

• Machine/facility time is often considered a scarce resource
• More frequent setups mean less productive time
• Larger batches maximize productive time
• Traditional view: “The machine should never be idle.”

Impact on Inventory Levels

These long setup times and resulting large batch sizes create several inventory-related problems:

1. Work-in-Process (WIP) Inventory

• Large batches mean more units moving through the system
• Each work station holds more inventory
• Longer production cycles(per Little’s Law)
• More space required for WIP storage

2. Finished Goods Inventory

• Large production runs create excess finished goods
• Products may sit in inventory for extended periods, leading to
  • Higher holding costs
  • Increased risk of obsolescence

3. Supply Chain Effects

• Suppliers also tend to produce in large batches
• Raw material inventories increase
• Longer lead times throughout the supply chain
• Less flexibility to respond to changes

This traditional approach to managing setup times creates a self-reinforcing cycle:

Long setup times → Larger batch sizes → Higher inventory levels → More storage space →Higher costs → Pressure to reduce per-unit costs → Even larger batch sizes

Balancing Setup and Holding Costs: The EOQ Principle

After understanding how setup times influence batch sizes, we can explore how to find the optimal balance between setup costs and holding costs using the Economic Order Quantity(EOQ) model.

The Basic Trade-off:

1.Setup/Ordering Costs (decreases with larger batches)

• Fixed cost per setup/order
• More frequent setups = higher total setup costs
• The bigger the batch (or order), the lower the marginal costs associated with each unit

2. Holding Costs (increases with larger batches)

• Bigger batches mean higher inventory carrying costs
  • Storage space
  • Capital tied up in inventory
  • Risk of obsolescence
  • Insurance and handling

The EOQ Formula

The classic EOQ formula finds the optimal batch size where total costs are minimized:

Where:

• D =Number of units demanded, or total number of items needed
• S =Setup/ordering cost per batch
• H =Holding cost per unit per time period of the demand

The time period could be a day, a month, or a year. Whatever the time period is, it needs to be the same for both D and H.

Example:

Annual demand = 10,000 units

Setup cost = $100 per batch

Holding cost = $2 per unit per year

EOQ = √((2 × 10,000 × 100)/2) = 1,000 units

Visual Representation of the Trade-off:

Total Cost = Setup Cost + Holding Cost

• Setup Cost curve decreases as batch size increases
• Holding Cost curve increases as batch size increases
• Total Cost curve is U-shaped
• Minimum point represents the EOQ

Note that the EOQ formula works for two questions:

1. How much should I make or do in a batch if there is a setup time (cost) associated with every batch.

• In this case, the X axis or answer to the equation is “batch size”

2. How much should I order of an inventory item that needs replenishment regularly and that has an ordering cost associated with it.

• In this case the x-axis or answer to the equation is “order quantity”

Setup Time’s Impact and the Journey to Single Piece Flow

The EOQ formula reveals a fundamental truth about operations: as setup times decrease, the economically optimal batch size also decreases. This mathematical relationship points toward an ideal state where, with zero setup time, we could process single units with maximum efficiency. This insight forms the theoretical foundation for single piece flow and drives the importance of setup time reduction.

Single piece flow represents a state of perfect operational flow, where work moves through a system one unit at a time, much like water flowing smoothly through a pipe. In manufacturing, this might mean a single product moves from station to station with no waiting time between operations. In a service setting, imagine a patient moving through a series of medical tests and consultations without delays, or a document processing center where each case flows immediately to the next step once completed.

The beauty of single-piece flow lies in its elimination of waste and its immediate feedback on quality. When work moves one piece at a time, quality issues become immediately apparent- there’s no large batch of defective items to discover later. This continuous flow also dramatically reduces lead times and work-in-process inventory, while increasing flexibility to respond to changing customer demands.

Key characteristics of single piece flow:

• Each item moves immediately to the next operation
• No waiting time between operations
• No accumulation of WIP inventory
• Immediate detection of quality issues
• Quick response to changes in demand

Reducing Set-up Times-SMED

However, the reality of most operations makes perfect single piece flow difficult to achieve immediately. Setup times- whether they involve changing dies in manufacturing, preparing rooms in healthcare, or resetting systems in services- create natural barriers to continuous flow. This is where SMED (Single Minute Exchange of Dies) becomes crucial as a systematic approach to reducing these barriers.

SMED methodology begins with a fundamental distinction between internal and external setup activities.

Internal setup steps must occur while the process is stopped-like changing a die in a press or preparing an operating room between surgeries.

External setup steps can be performed while the process continues running-such as preparing the next die or gathering surgical instruments for the next case.

The first step in SMED is simply identifying and separating these activities.

The next phase involves converting as many internal setup activities to external ones as possible. In a restaurant, this might mean preparing dinner service items while lunch service continues. In manufacturing, it could involve pre-heating tools or pre-assembling components while the current production run continues. This conversion often requires creative thinking and careful analysis of each setup step.

Mise en place, the culinary practice of gathering and preparing all ingredients and equipment before cooking begins, exemplifies the conversion of internal setup activities to external ones. Rather than stopping during service to chop vegetables, measure spices, or locate utensils- all activities that would traditionally interrupt flow- these tasks are completed during slower periods before service begins. This preparation transforms what would be internal setup time (done while cooking is stopped) into external setup time (done while other activities continue), allowing for smoother service and something closer to single-piece flow during peak periods. When properly executed, mise en place enables cooks to focus entirely on cooking and plating during service, moving each order through the kitchen with minimal interruption or delay.

For those setup activities that must remain internal, SMED focuses on streamlining and simplifying. Quick-release mechanisms replace bolts, standardized settings eliminate adjustment time, and visual guides reduce decision-making time. In service operations, this might involve standardized room setup kits or checklist-driven procedures that eliminate guesswork and reduce variability.

The principles of SMED extend far beyond its origins in manufacturing die changes. A hospital applying SMED to operating room turnover might develop standardized cleanup kits, preprepared instrument sets, and parallel processing of room cleaning and instrument preparation. A classroom might use mobile cart systems and standardized technology setups to quickly switch between different types of lessons. A restaurant might redesign its kitchen stations with quick-change mechanisms for different menu periods.

The ultimate goal isn’t necessarily to achieve perfect single piece flow immediately, but rather to continuously reduce setup times to allow for smaller batch sizes and greater flexibility. Each reduction in setup time brings operations closer to the ideal of single piece flow, with its attendant benefits of reduced inventory, shorter lead times, better quality, and improved customer responsiveness.

This journey from large batch operations to something approaching single piece flow represents a fundamental shift in operational thinking. Rather than accepting long setup times as a fixed constraint that forces large batch sizes, organizations can systematically reduce these times, moving closer to the ideal of continuous flow while reaping incremental benefits along the way.

Just-in-Time Production: Synchronizing Operations with Demand

Just-in-Time (JIT) production represents a fundamental shift in operational thinking, movingaway from traditional batch-and-queue methods toward a system that produces exactly what isneeded, precisely when needed. This approach emerged from Toyota’s production system but has since found applications across manufacturing and service industries.

At its core, JIT is about synchronization. Rather than producing based on forecasts andmaintaining buffer inventories, JIT systems respond directly to actual customer demand. This responsiveness extends beyond final assembly- each upstream process produces only what its downstream customer needs, creating a chain of linked processes all moving in rhythm with end customer demand.

Understanding Kanban Systems: Visual Control in Action

Kanban systems serve as the nervous system of JIT operations. Kanban, which literally means”signboard” or “visual signal” in Japanese, is a method of controlling and coordinating the production and movement of materials through visual signals. While the concept is simple, its effective implementation creates a powerful system for managing flow and controlling inventory.

A basic Kanban system operates using cards or other visual signals that authorize either the production or movement of materials. Imagine a supermarket shelf as a simple example. When a customer takes a product, it creates an empty space. This empty space is itself a visual signal(a Kanban) that triggers replenishment. The shelf space acts as a natural control on inventory- you can’t overfill beyond the allocated space, and you know to replenish when space becomes available.

In a manufacturing setting, a two-card Kanban system is common. The first type of card, a production Kanban, authorizes a workstation to produce more of a specific item. The second type, a withdrawal Kanban, authorizes the movement of materials from one location to another.

Here’s how it works:

When a downstream process uses materials from its inventory location, it removes the withdrawal Kanban card attached to those materials and sends it back to the supplying process. This card signals the authorization to withdraw more materials from the supplier’s finished goods inventory. When the supplier’s finished goods are withdrawn, the production Kanban card attached to those goods is removed, authorizing the supplier to produce more.

Consider a practical example in an auto parts factory. An assembly line uses brake components stored in small bins. Each bin has a withdrawal Kanban card. When a bin is emptied, the card is sent to the brake component production area. This triggers the release of a full bin to the assembly line. The production area, seeing its inventory of finished brake components reduced, uses its production Kanban to authorize making more components.

In service operations, Kanban systems might look different but follow the same principles. A hospital surgery department might use a two-bin system for surgical supplies. When the first bin is empty, it signals the need for replenishment while the second bin provides supplies during the replenishment lead time. The empty bin itself serves as the Kanban signal.

Modern implementations often use electronic Kanban systems where physical cards are replaced by electronic signals, but the principles remain the same. These systems can provide real-time visibility of material flow and automatically trigger replenishment orders.

The beauty of Kanban lies in its visual nature and simplicity. Workers can see at a glance what needs to be produced or moved. Problems become immediately visible when cards start accumulating at a workstation, indicating a bottleneck. This visibility facilitates quick response and problem-solving.