CI-Gabriel, an automotive ride control product manufacturer, faced cleaning inefficiencies with their industrial washing machines. A student team used Flownex to simulate and optimize water flow and pressure in a new washing machine design, improving spray coverage from 28% to 86%, increasing impact force 2.87 times, and reducing cycle times for better efficiency and contaminant removal.
CUSTOMER PROFILE
CI-Gabriel manufactures, distributes, and supplies the automotive market with ride control products, including:
Shock absorbers.
Struts.
Gas springs.
The company produces approximately 10,000 units daily to meet both industrial and aftermarket demand in Southern Africa.
CHALLENGE
During manufacturing, tubular parts undergo machining and welding. These components must be cleaned to remove dirt, loose metal pieces, and contaminants. The existing washing machines were failing to remove these contaminants sufficiently, leading to several issues:
Quality Risks: Residual contaminants could lead to rejected components after assembly.
Resource Waste: Potential loss of income and wasted raw materials.
Inefficiency: High water and chemical consumption with poor spray coverage (only ~28%).
SOLUTION
Through use of Flownex, the team was able to determine if the design met the required specifications, and also realized significant improvements to the previous industrial washing machine system.
INTRODUCTION
Global Engineering Teams (GET) is an academic initiative between numerous universities and companies worldwide. In the GET program, groups of students complete projects for industrial partners as part of their academic studies. One of the industrial partners, Control Instruments (CI)-Gabriel, had an ineffective industrial washing machine that was used on the plant to clean cylindrical struts. CI-Gabriel tasked one of the groups to design an improved and optimized industrial washing machine. The washing machine design that the group proposed used pressurized water and was a mesh of pipes with spray nozzles at several points. The group needed to know the flow rates and the pressure at the nozzles to ensure that the design met with the client specifications. The current spray system has poor coverage of the struts. Impact force from the sprayed water is also low due to poor nozzle choice.
The washing machines that GI-Gabriel currently employ, do not remove these contaminants sufficiently. The amount of water consumption and use of chemicals are other concerns with the current machines. CI-Gabriel challenged one of the GET groups to design a new inline automated washing machine. The pressurized water enters the pipe networks at the flexible inlet pipe from a high pressure pump. One strut is shown going through the machine and the light blue triangles represent water jets flushing away dirt from it. The washing machine can move vertically upwards and downwards, hence the flexible inlet connection pipe. This allows for the lower tubes to enter the struts to clean internal surfaces as well. The team now needed to size the washing machine’s components and then determine pressure and mass flow rates through the nozzles. They also had to evaluate if the proposed design would clean sufficiently and effectively.
SOLUTION
To ensure that the design met with the client specifications, the group made use of the student version of Flownex to simulate their design. The washing machine was split into two networks for simulation:
The system layout, which includes all flow components as well as the pipe network, which distributed the cleansing water around dirty parts.
The split networks enabled different members of the team to work on the networks simultaneously. It also allowed for closer study of flow at the nozzles on a compact network.
The secondary pump draws water from the secondary reservoir. This water is filtered and then flows into the main reservoir, where it is heated to 55°C by heating elements. The main pump circulates the water. If the solenoid valve is closed, water is pumped into an accumulator. When the valve is opened, the water flows to the pipe network with spray nozzles and cleans the dirty tubes. The function of the accumulator is to allow the pump-and-motor to run continuously and to allow for use of a much smaller pump. During the 36 seconds cycle, the accumulator is charged for 18 seconds and discharges for the remaining 18 seconds.
The pipe network was modelled from the solenoid valve. The nozzles were modelled as restrictors, with their exits at atmospheric pressure. Pressure at the flexible inlet hose was specified as 6200 kPa, which is the pump outlet pressure. The benefits of using Flownex for the simulation were:
Tedious manual calculation of pressures and flow rates at the nozzles were avoided.
The team could accurately determine where to place the nozzles to ensure that the flow is evenly distributed through use of the designer feature in Flownex.
The cyclic operation for the washing machine could be fully simulated.
Performance characteristics of the new system could be compared to the old system in the design phase. This helped to ensure that the final design performed satisfactorily. The earlier design changes are made the more affordable the changes are.
A result layer shows the results from the simulation. Mass flow rates at the nozzle are shown to be evenly distributed, averaging 0.102 kg/s.
RESULTS AND BENEFITS
The use of Flownex allowed the team to compare the new system's performance against the old one during the design phase, making changes more affordable.
KEY PERFORMANCE IMPROVEMENT
With the help of the Flownex, the team was able to achieve the following:
- The optimum point of the system was determined to be 6.2 L/min per nozzle at 60 bar.
- Water consumption rate increased by 6%, but total consumption is lowered due to shorter cycle times.
- 86% direct spray coverage against ~28% for the old system.
- Impact force of the water increased 2.87 times.
Starting at the bottom left of the figure and going anti-clockwise, the graphs are:
The fraction that the solenoid valve is open. It fully opens and fully closes every 18 seconds.
Pressure at the pump exit. Use of an accumulator soothes this graph. When the simulation period is extended, the graph becomes even smoother as the initial transient characteristics die out.
Pressure at the exit of the solenoid valve. Results from this graph were important in selecting the solenoid valve to use.
Mass flow rate through the solenoid valve. An average of the graph’s crests is close to the 2.8 kg/s minimum flow required.
Pressure at the inlet of the solenoid valve. It peaks at 7300 kPa right after the valve is closed. It then drops gradually as flow is diverted to the accumulator. When the valve opens again, it suddenly drops again.
CONCLUSION
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A team of students designed a new industrial washing machine for CI-Gabriel in an academic study. The team simulated their design in Flownex, which they used to determine the optimum operating point of the system. They also used the results from Flownex to position the nozzles and ensure that the flow was evenly spread out. Simulation of the cyclic operation of the washing helped the team determine water and energy consumptions, as well as the overall efficiency of the washing machine. Through use of Flownex, the team was able to determine if the design met the required specifications, and also realized significant improvements to the
previous industrial washing machine system.
PROFILE
In Global Engineering Teams (GET), a multidisciplinary intercultural team which consists of at least 4 students works on a project that is offered by an industrial company. Academic partners include The Technical University of Berlin in Germany, Sociesc in Brazil, University of Stellenbosch in South Africa as well as partners in Botswana,
Nicaragua and Puerto Rico. Partners from industry include Daimler Chrysler, Whirlpool, CI-Gabriel, Inpro, BMW etc. These projects are typically design or research projects, which are to be completed within an academic calendar year. The team that used the Flownex software to design an industrial machine consisted of 6 members, 2 from South Africa, 2 from Germany and 2 from Brazil.