Are there any case studies on injection molding parameter optimization?

Case Study 1: Optimisation and Efficiency Enhancement of Transparent Personal Computer Products

Project Background: A polycarbonate transparent product injection moulding plant in Zhejiang Province was deemed inefficient due to its original moulding cycle of 50.7 seconds and daily production capacity of 284 pieces/hour.

Parameter Optimisation Measures: The plant conducted mould temperature balance and extreme cooling experiments, implemented minor mould structure modifications, and optimised equipment TPM. Additionally, it optimised internal parameters using Young's injection moulding rapid prototyping method.

Implementation Results: The moulding cycle was shortened to 32.5 seconds, the daily production capacity was increased to 443 pieces/hour, the overall production efficiency was enhanced by 56%, and the product yield remained consistently high.

Case Study 2: Optimisation of Shrinkage Marks/Internal Stress Defects in PA66 Products

Background of the Project: The PA66 plastic shell exhibited substantial shrinkage markings on its surface. Gears that were injection moulded with PA66 were deformed and warped following demolding, which had an impact on the product's dimensional accuracy and appearance.


Project Background: Parameter optimisation actions: The holding pressure was increased from 30MPa to 40MPa, the holding time was extended from 5 seconds to 10 seconds, the mould temperature was increased from 40℃ to 60℃, the injection speed was reduced from 80% to 60%, and the injection pressure was reduced from 90MPa to 70MPa. These changes were implemented in conjunction with optimised uniform cooling channels.

Results of implementation: The product yield increased from 75% to 98%, gear internal stress was substantially reduced, warpage was resolved, and surface shrinkage marks on products were completely eliminated.

Case Study3: Intelligent Optimisation of Injection Moulding Machines Using Digital Parameters

Project Background: The traditional method of manual parameter adjustment is dependent on experience, which leads to low efficiency, high energy consumption of apparatus, and significant industry pain points.

Injection moulding machine operating data was collected through equipment IoT by utilising the COSMOPlat industrial internet platform. Parameter optimisation actions were implemented. An intelligent algorithm was developed to autonomously optimise the energy consumption and cycle time parameters of the injection moulding machine by recommending process parameters based on a large industrial model.

Implementation Results: The average energy consumption of injection moulding machines decreased by 10% in actual factory production, while the overall production cycle time increased by 6%. The long-term stable and efficient operation was achieved without the necessity of repetitive manual trial and error adjustments.

The precision hot runner multi-cavity mould injection moulding production line you are currently maintaining is fully compatible with the optimisation logic of these cases. These solutions can be directly referenced and reused by ordinary maintenance engineers to expedite the process of reducing waste and increasing efficiency.