Just in time (JIT) manufacturing is a workflow methodology aimed at reducing flow times within production systems, as well as response times from suppliers and to customers. Conceptually, it is the same as Lean Manufacturing and the Toyota Production System.  As such, it is prudent to reflect somewhat on the considerably known and accepted Mass Production System initiated by Henry Ford.

The primary objective of mass production is to produce the largest possible lot size possible relative to marketing forecast models. This is an inherent model that pushes products from the front of the production process to warehouses, to the customer. The mass production system requires huge stockpiles of raw material, work in progress(WIP), and finished goods inventory. These assets carry a stupendous cost, from spoilage, theft, obsolesce, and mask the hidden factory.

The Just in Time System – A Pull System

The Just in Time System developed primarily by Taiichi Ohno is a pull system. Its primary objective is to pull product from the trough the system, in small lots, making only what is requested, nothing more, nothing less.  Ohno carefully studied the Ford Model and noticed seven wastes in appalling magnitudes:

  1. Transportation
  2. Inventory (WIP, raw materials, and finished goods stored in expensive warehouses)
  3. Motion
  4. Overproduction
  5. Over-processing
  6. Waiting
  7. Defects.

His priority was to design the JIT System so that the seven wastes would be virtually eradicated.

Critical Problems from JIT
Three critical problems, perhaps a major triple constraint, arose concerning the JIT System:
  1. Machine Problems
  2. Process Problems
  3. Lot Size Constraints.

In the concept of mass production, the first two issues are handled by having huge amounts of safety stock, just in case these failures occur. Machine failures in a JIT environment can be disastrous, as there is very little buffer inventory on hand to fill orders, and the financial impact can be exponential. Ohno neutralized this problem by enjoining TPM (Total Production Maintenance) to the JIT System. Machines are kept in top shape by using predictive maintenance and changing parts before they fail; operators are trained to have close technical intimacy and understanding of their equipment.

Process Problems in a JIT

Process Problems in a JIT environment can be exponentially crippling again because there is little or no safety stock on hand to cover pending customers. Ohno solved this constraint in his organization by engaging employees and management to deeply study and analyze their processes using various tools, including Fish Bone diagrams, Control charts, Pareto charts, Failure Mode, and Effects Analysis, to name a few.

Lot sizes in mass production are usually huge, and inventory reserves are enormous, just in case machines fail. JIT systems initially faced extremely high setup costs; the smaller the lot size, the higher the per unit setup cost. Ohno solved this problem by developing and deploying SMED (single-minute exchange of dies), which dramatically reduced setup costs.

The Requirements of JIT are:
  1. Proper organization (5S deployment)
  2. Development of talent
  3. Deploying a simplified flow
  4. Leveraging Kanban to pivot order fulfillment
  5. Visual management
  6. Breaking Constraints and Bottlenecks
  7. Small lot sizes
  8. Setup time reduction (SMED)
  9. TPM
  10. Process Management
  11. Supplier Management
  12. Waste Reduction Management

At a local bakery, we used a push production system for manufacturing our frozen bread. The Production department controlled the flow of the entire operation, and the Packing, Purchasing, and Warehouse departments were subordinate departments. Consequently, the packing department overpacked bread, and the warehouse department struggled to manage the inventory.

Mini Case Study:
The following was the problem statement concerning incorrect inventory.

Over the last 26 days, the Warehouse Operations Inventory Counts have yielded 717 misreported cases out of 44,063. As a result, there was over-production, short ships and expedited shipments costing XYZ Bakery $38,953 for the period (Potential Annual Impact $546,840).

An agreement was reached to have the Warehouse Department (the end of the process) use Kanbans and eKanbans to pull packed products requested by customers from the packing department, who will, in turn, use Kanbans to signal to the production department to produce. We produced the customer orders in the quantities requested, nothing more, nothing less. The Warehouse Department is no longer overwhelmed by a powerful production process that pushed products through the system and never runs out of space in the freezers. We utilized takt time, 5S, value stream mapping, Pareto charts, fishbone diagrams, FMEA, and control charts to improve the processes, which are now almost 6 sigma level.


  • Goetsch, D.L, Davis, S.B. (2010). Quality Management for Organizational Excellence. Introduction to Total Quality. Prentice-Hall, Columbus, Ohio

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