Simulation a valuable tool in proof-testing designs
By Glen Barnes

Glenn Barnes, Manager Logistics Consulting, Dematic Pty Ltd has more than 20 year’s experience in the design and operation of integrated logistics and materials handling systems.

In the following article he details the value of computer simulation in optimising the design of material flow systems. Dematic has used computer simulation of material flow systems in manufacturing and distribution logistics applications for over 10 years, and utilises the latest abstract modelling tools to deliver designs faster, and at a lower cost.

The most important thing to understand about simulation is that it is a validation tool, not a design tool.

Critical information such as the type of products to be handled, likely throughputs, growth projections, service levels, physical and financial constraints, all has to be analysed before we can begin to evaluate alternative design concepts. Only when we have determined the preferred design concept does simulation come into the picture.

Simulate Only What is Necessary to Prove the Design

Simulation is a powerful tool for assessing how an automated materials handling solution would perform under a wide range of design and operating conditions. It enables us to try different combinations of technologies and processes to optimise our design.

At Dematic, we take the view that it is often unnecessary to simulate complete systems. Combined with our depth of design experience, simulation makes it more efficient to prove only those areas where there is some uncertainty.

These areas are typically points of interaction between machines, or man and machine, where performance variables can significantly influence the outcome.

We already know at what speed certain types of equipment such as conveyors will run, so there is little value to be gained in simulating such a process on its own. What we can’t tell when we look at a design on paper, is where will the weak points of the system be? How do we build redundancy into the system? How many metres of accumulation does the conveyor system feeding the robotic palletiser need? Will one person be able to handle the stream of goods coming down the conveyor line for palletising, or will it take two?

These are the types of questions that only simulation can help to answer, which is why when we build the model, we integrate flexibility into the areas we know we will need to tweak. In our simulation models, we literally create a series of dials where we can test different scenarios by increasing and decreasing the variables and the way they interact.



Material Flow Simulation in Action

The ability to test various ‘what-if’ scenarios was particularly useful on a recent simulation project conducted by Dematic in conjunction with and on behalf of Masterfoods Australia New Zealand (ANZ).

Masterfoods ANZ was upgrading its despatch warehouse systems, including conveyors and automated palletising equipment at the company’s production plant in Ballarat, Victoria.  The plant produces a variety of products including Snickers, Mars bars and other types of confectionery in various package sizes. Finished goods from production feed into the despatch warehouse via three conveyors, with each line capable of carrying a mixed stream of products.  It is essential that the despatch area works efficiently. Any hold-ups or delays in palletising has a flow on effect to the production lines. If the delay in the despatch area is long enough, it will cause production to halt.

To be able to prove that the design for a new conveyor sortation system, laser guided vehicle (LGV) and robotic palletising system that Masterfoods ANZ was considering, would meet its projected handling and throughput levels, the creation of a sophisticated computer model of the proposed equipment and systems was necessary.



The recommended maximum utilisation of 85% is shown in red.
Product A Scenario: Wrapper Utilisation (Maximum / Average) 99% / 67%
Product B Scenario: Wrapper Utilisation (Maximum / Average) 83% / 55%
The simulation demonstrated that the system comfortably handles both design levels. However, the stretch wrapper does run at nearly 100% utilisation at several occasions during the “Product A” scenario, and will become a bottleneck if the rates are increased.

Objectives of Simulation

The objective of the simulation project was to:

• Evaluate the proposed system design for various production scenarios
• Validate if the system was capable of meeting Masterfoods ANZ’s design requirements with the given scenarios.
• Quantify the effect of equipment downtime (due to maintenance or failure)
• Provide a tool for Masterfoods ANZ to evaluate custom production scenarios in the future.

First Step to Simulation

The first step in producing the simulation was for engineers from Dematic to conduct a thorough site survey in which they accurately measured the physical location of various elements, including an existing strapping machine that would have to interface with the new systems.

The engineers also recorded the operating speeds of all equipment, and captured all likely product package dimensions and weights.

At the core of the simulation model used by Dematic is a database that drives the analysis. In preparing the comprehensive simulation package for Masterfoods ANZ at Ballarat, Dematic created a database of all of the different products the company makes at the plant, taking into account their physical dimensions and establishing the various palletising patterns that could be used for the different products. Dematic also had to create numerical models of each of the various pieces of equipment that would form part of the overall system.

Simulation Provides Design Flexibility

Once set-up, the simulation allowed many system parameters to be modified through the use of simple input text files, such as:

• Product dimensions, production rates, palletising patterns and sorter lane allocation for each product
• Pickoff carton sequence and times for each palletising pattern (max. 40 patterns)
• Manual palletising rate and machine cycle times.

Identifying Problems Before They Happen

A key feature of the simulation model is its ability to accurately assess machine utilisation. The goal in most production-related operations is to keep maximum machine utilisation around 80%. When utilisation rates get higher than this, the likelihood of problems increases. A feature of the simulation model is that you can very quickly see what effect even a simple change, such as slightly increasing the speed of the conveyors delivering product to the despatch area, would have on the utilisation rate of the different pieces of equipment within the area.

Using the existing stretch wrapper as an example, the simulation to the design levels provided by Masterfoods ANZ indicated that the stretch wrapper could become a potential bottleneck.

What-If Scenarios with Simulation

A key feature of the simulation model is the ability to run ‘what-if’ scenarios.  This enabled Dematic and Masterfoods ANZ to look at the impact that changing the various mix of product would have on the efficiency of the system that was being evaluated.

The computer simulation package made it very easy for the users to identify that if “we did ‘A’ at ‘B’, it could lead to problems and potential bottlenecks at ‘C’”. It is also an easy process to very quickly determine the effect that any equipment stoppages would have on overall system performance. For example, by running a breakdown analysis on all of the individual pieces of equipment, it was possible to see what effect their stoppage would have on the operation as a whole.

From running these scenarios, Dematic and Masterfoods ANZ could very accurately determine exactly how long it would take for an equipment failure to bring production to a halt, and how long it would take until the system would be back up and running at normal capacity.

Award-Winning Performance

The advanced simulation developed by Dematic and Masterfoods ANZ won the Manufacturing Logistics Award in the LAA’s 2005 National Logistics and Supply Chain Awards.

Receiving the award, Masterfoods Engineering Controls and Information Technology Manager, Damien McCarthy, said: “As well as the simulation being able to assess the performance of the planned equipment and systems, Dematic engineers realised that in creating the simulation package, they had also created a unique tool that Masterfoods could continue to use for a variety of purposes, including production scheduling.

“Being able to tinker with production run rates and volumes makes it possible for us to accurately assess the impact of changing the production mix at any time, giving us the tools to balance the workflow across the system to maximise efficiency, throughput and productivity,” he said.

For more information, please contact Glen Barnes:

glenn.barnes@dematic.com
Ph. 61 (0) 407 276 396