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A Perspective of the Manufacturing Future: Inventory Management

Get an industry analyst's look at how IoT will shape and change the way manufacturers handle inventory.

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This is the third post 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 through utilizing what we know to be technically possible today. So far I have covered cutting tools for machining and production management.

In this post, I am 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 using models/simulations to make recommendations for the most impactful 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/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.

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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 through manual processes. 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 utilized to more accurately determine necessary buffer sizes.

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

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 utilize 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 utilized to determine where constraints will arise based on current and forecasted production schedules. These models will be improved and will learn by utilizing 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 linkages between data systems and influences on scheduling. These simulations will provide scheduling with inputs necessary to drive minimum amounts of inventory.

This has been another post on my perspective of the manufacturing future. In this post I’ve discussed how data systems, modeling, and simulations will be used to minimize the amount of inventory that manufacturers need. Lower inventories will reduce the amount of cash and other resources that are tied-up in inventories and lower costs associated with maintaining the inventory.

My next post will describe my perspective of the future for quality management and then I'll wrap-up this series with a post on the value of each of these initiatives. Please be sure to come back to read those posts.

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Topics:
iiot ,inventory ,manufacturing

Published at DZone with permission of Andy Henderson, DZone MVB. See the original article here.

Opinions expressed by DZone contributors are their own.

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