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Case Studies

CASE #1: Planning and re-engineering with AutoMod

The demand is very dynamic, our production is increasing, and all our customers insist on being supplied Just In Time.

Situation:

This company has plants in Japan, the United States and Canada. It is a supplier of components for the automotive industry and counts the major players in this industry among its customers. After stamping and welding operations, the products are loaded onto a Power & Free Conveyor to be carried from the manufacturing area towards the painting and chemical coating rooms where are treated after being automatically transferred on a chain conveyor. When they leave the area, they are loaded onto the Power & Free Conveyor and directed into the stock room before they are sent to the final assembly and shipping area where they are unloaded from the conveyor. The total cycle time is longer than the expected response time required by the customers. Also, the demand is very dynamic and orders are changed frequently, so the company must maintain a significant inventory of WIP between the paint and the assembly area.

Problem:

With such a dynamic demand and a forecasted new increase in the production, how will it be possible to reconfigure the Power & Free Conveyor, the backbone of the entire plant, so that we can the same time minimize our WIP and improve the response time to our customers?

Solution:

Accurate 3D simulation with the ability to represent P&F and chain conveyors was a prerequisite to answer this question. This is why AutoMod was chosen. The model developed by MultiCIM is focused around the conveyors systems (P&F and chain conveyor). AutoMod has allowed us to represent both the complex logic and the detail up to the level of individual components being loaded on racks. Up to two months of detailed production forecasts can be simulated within minutes. Once validated against real-life results, this model has been used to demonstrate the interest on reconfiguring critical areas of the conveyor systems.

Among the scenarios tested, the addition of spurs sections at the loading booths showed an improvement of 12% on the response time for the concerned parts. The model did not show significant improvements in the throughput when the same approach was tested at the unloading stations, proving that this would have been an unnecessary investment. On another hand, the simulations demonstrated that the company should consider changing the organization of the stock area before assembly, as some scenarios proved its layout not to be as efficient as it could have been, thus forcing the company to maintain a higher WIP than necessary to achieve the required level of service. After quantifying the impact of various changes on the system's performance, the model was enhanced to include a proposed addition for the production of a new product line and validate the new P&F conveyor layout. Finally, due to the flexible approach used to develop the model (external data files edited through Excel), it has been utilized since by the company for testing and validating new planning and mix strategies.

CASE #2: Validating an automated conveyor system with AutoMod

Can we ship 3,500 orders in 8 hours( vs. 1,900 today) with our new and fully automated conveyor system?

Situation:

This company which specializes in 24hr office product on-site delivery has forecasted an increase in its demand in the next months. In order to be able to cope with it, it has just bought and installed a new fully automated conveyor system (PLC driven, photocell and scanner controlled, with scales etc.). This conveyor is in charge of circulating totes around the picking zones where employees are loading them with the appropriate quantity of the required items. Once an order is fulfilled, the tote is sent to an inspection and packaging counter where its contents is controlled and sent to the shipping dock while the empty tote is sent back into the loop (if necessary).

Problem:

Proving to be perfectly efficient at the current level of activity, how can we make sure the system will be able to deal with a 75% increase on the demand ? This question, despite the optimism of the conveyor manufacturer, was still an issue for the company which started to perform on-site simulations (!). But after some time (8 hours) and money consuming (hiring personnel to operate the system during the night) simulations of this sort the question was still unanswered.

Solution:

Due to its built-in expert material-handling modules, AutoMod was a perfect candidate to help the company answering this question. Within a day the entire layout and characteristics (speed, type of section, orientation end dimensions) of the conveyors were reproduced into AutoMod. The control logic and picking and control activities were added to the model and MultiCIM started testing demand scenarios against different configurations of the system. Once validated with the company and the conveyor supplier, within minutes, the AutoMod model was able to run an entire production shift of 6 to 11 hours (depending on the scenario) and was also giving more insight on the behavior of the system than the company had been able to obtain so far using other means. These statistics include the time in system, re-circulation rate, average hourly input and output, time in zone, average number of totes in zone, operators utilization as well as sections' specific statistics for the conveyor.

The simulations demonstrated that the system was not capable of handling the workload of 3,500 orders per day in less than 8 hours but rather in some 11 hours. But against all expectations, the major bottleneck was not really a specific area of the conveyor but rather the organization of the activities in the picking zones. As the totes were admitted by batches of 10 initially, the re-circulation rate and the time in system were very high. By making the picking a more fluid activity (i.e. batch of 1), an improvement of 30% on the original productivity was observed.

After this first result, different configurations were tested with various demand scenarios to find out the appropriate organization for each level of demand allowing the company to be aware of other potential bottlenecks. The model was also used to validate some aspects of the PLC's programs to enhance the routing of the totes on the conveyor.

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