What Is Optimized Production Technology?

Optimized production technology (OPT) is a production scheduling and management methodology developed by Eliyahu Goldratt in the late 1970s and commercialized through the 1980s. It addresses factory scheduling by identifying and managing the capacity constraint resources (bottlenecks) that limit the rate of output through an entire production system. OPT challenged the then-prevailing practice of maximizing machine utilization at every workstation, arguing instead that non-bottleneck resources should be subordinated to the pace of the bottleneck and never allowed to produce more inventory than the system can absorb. The methodology drew on operations research, queuing theory, and industrial engineering, and it evolved into the broader Theory of Constraints (TOC) framework that Goldratt later formalized in the 1984 book "The Goal."

OPT introduced nine operating principles, including the assertion that "an hour saved at a non-bottleneck is a mirage" and that "the level of utilization of a non-bottleneck resource is determined by other constraints in the system." These principles departed sharply from cost accounting approaches that evaluated performance by local efficiency metrics. The academic reception is documented in management science literature connecting OPT to theory of constraints and local optimization.

Bottleneck Identification and Management

At the foundation of OPT lies the concept that every production system contains at least one bottleneck, a resource whose capacity is insufficient to satisfy total demand, and that this constraint governs the throughput of the entire system. Identifying the bottleneck requires analysis of capacity data, queue lengths, and production records, a process OPT codified into the "drum-buffer-rope" (DBR) mechanism: the bottleneck sets the production drum, a time buffer protects the bottleneck from starvation caused by upstream variability, and a rope synchronizes material release at the start of the line to the bottleneck's rate. Activating a non-bottleneck beyond the rope's signal accumulates inventory without increasing throughput, which is the core insight separating OPT from earlier capacity-planning frameworks. A detailed description of these principles appears in Goldratt's foundational OPT framework analysis at the University of Technology.

Scheduling and Finite-Capacity Planning

OPT's scheduling module distinguished between bottleneck resources, which it scheduled forward from the drum rate using finite-capacity rules, and non-bottleneck resources, which were scheduled backward from the bottleneck's requirements. This two-pass approach contrasts with infinite-capacity planning systems such as Material Requirements Planning (MRP), which explode bills of materials without accounting for capacity limits, and can generate schedules that are infeasible in practice. The finite-capacity scheduling philosophy that OPT pioneered influenced subsequent advanced planning and scheduling (APS) software systems and helped drive the adoption of simulation-based scheduling in semiconductor fabrication, automotive assembly, and process industries.

Integration with Theory of Constraints

Goldratt generalized OPT into the Theory of Constraints (TOC) by extending the bottleneck concept from manufacturing to any system governed by a limiting factor, including project management, distribution, and sales. TOC introduces a five-step improvement cycle: identify the constraint, exploit it fully, subordinate all other decisions to it, elevate it if necessary, and then search for the new constraint. In production, this cycle maps directly to OPT's scheduling principles. Organizations implementing TOC have reported reductions in lead time, work-in-process inventory, and operating expense, as reviewed in the Theory of Constraints literature synthesized by the Lean Production community.

Applications

Optimized production technology has applications in a wide range of fields, including:

• Production planning in discrete manufacturing, replacing infinite-capacity MRP scheduling
• Production system design, locating and relieving bottleneck workstations
• Semiconductor wafer fabrication, scheduling equipment-constrained process flows
• Automotive assembly, synchronizing subassembly feeder lines to the main assembly drum
• Project management, applying the critical chain method to multi-resource projects