A Perspective of the Manufacturing Future,
Part 3

Inventory management

Published: Wednesday, November 16, 2016 - 11:10

This is the third part in a series about my perspective of what the future has in store for various aspects of manufacturing. I approached each aspect by imagining what is possible using what we know to be technically possible today. In part one I covered cutting tools for machining and in part two production management.

In this article, I’m going to present a future where inventory (including any material in the production process) is maintained at the lowest possible levels through data systems that analyze real product flow for statistical variability, constraint identification, and by using models and simulations to make recommendations for the most useful improvement opportunities.

Current state

Most manufacturing organizations subscribe to and follow the principles of lean manufacturing. However, changing customer demands, unpredictability in the supply chain, long lead times, and quality issues lead to disruptions and subsequent adjustments in the process. Those adjustments are often made on a micro scale with little or no visibility into the macro effects.

Also, as constraints or bottlenecks shift from one operation to another within the manufacturing process, they may be difficult to track, especially in complex processes.

The variability and unpredictability in the total supply chain drives manufacturers to create buffers of parts. Cash is tied up in the inventory itself, and there are costs associated with handling and storing inventory.

Process analysis will provide insight into where bottlenecks are by analyzing the queues for the various operations. If a process is adjusted, the analysis system will provide feedback on the process at a “global” level.

Process analysis

Process analysis will depend on unprecedented feedback from the manufacturing process. In regards to inventory control, the feedback will come from part tracking through the process and order/job tracking. Through digital systems, each part will be tracked through every step of the process—which would be nearly impossible using manual methods. The ability to track individual parts through their manufacturing process, and being able to compare actual processing times with expected processing times, will provide insight into real statistical variability in the manufacturing process. This real variability will be used to more accurately determine necessary buffer sizes.

Bottlenecks can shift from one operation to another depending on the mix of parts within the process, the capabilities of the available production equipment, and the routings involved. They can also shift due to improvements at an operation.

The analysis will determine the true speed of the bottleneck, and this will be used to drive the speed at which the entire process operates. The analysis system will also use the tracking information to create the “pull” signal for upstream operations that indicates some buffer at the constraint has been processed and needs to be replaced.

Modeling and simulations

Process models and simulations will be used to determine where constraints will arise based on current and forecasted production schedules. These models will be improved and will “learn” by using the data coming from the process analysis. By knowing the real process variability combined with the expected flow through the process, simulations will be able to predict where constraints will be before they arise. Manufacturing personnel will be able to plan and investigate solutions preemptively.

Simulations will also rely on data connections with scheduling and routing. In my previous post on production scheduling, I described links between data systems and their influences on scheduling. These simulations will provide scheduling with inputs necessary to drive minimum amounts of inventory.

Lower inventories will reduce the amount of cash and other resources that are tied up in inventories and lower the costs associated with maintaining the inventory.

First published on the GE Digital blog.

About The Author

Andy Henderson

As an industry analyst at GE Digital, Andy Henderson leverages his experience from his time as an advanced manufacturing engineer within GE Power and his research during his doctoral program to promote a vision for the future of heavy industry/discrete manufacturing and drive strategy for achieving that vision.