China as a tire manufacturing country, rubber tire annual output is huge, but faces the problem of big but not strong, and the gap with the international tire giants is very obvious. Because the price of domestic tires is much lower than foreign brands, China's tire exports are often subject to anti-dumping and other trade protection measures. Therefore, improving product quality, expanding high-end market share and increasing profit margins is the current problem faced by enterprises. Tire is a safety product, the quality of uneven distribution of tires in high-speed rotation, unbalanced centrifugal force will cause vibration of the car body, the car's handling performance, safety performance and ride comfort will be reduced, while the noise increases.

Forming is a crucial process in the tire production process, the semi-finished parts according to the process requirements for the combination of bad tire. Tire bad quality directly determines the quality of the tire, is an important indicator to measure whether the tire is qualified or not, so real-time monitoring of the quality of the tire blank is necessary according to the tire bad quality standards for online testing and analysis, screening out unqualified tire bad and alarm, prompting the process personnel to deal with, so as to optimize the production process, standardize the process control procedures, in order to reduce the emergence of defective products, and significantly improve product quality. This program in-depth analysis of the tire blank production process, based on the development of supporting bad tire feeding system, combined with the operation process to achieve effective control of the quality of the bad tire.

1 Hardware system architecture design

This dosing system adopts a layered structure design system, first of all, the application of three-dimensional digital design and manufacturing technology, digital modeling, debugging and optimization as a means of digital modeling, and integrated design, analysis and data processing, the use of the analysis and calculation results obtained to ensure that the elastic element structure design is the most reasonable, the performance fluctuations are minimized, to ensure that the structural design of the weighing module of the loading system and the reasonableness of the manufacturing. Tire clamping workpiece is made based on the platform of the tire blank weighing, the workpiece adopts the adjustable way to adapt to the weighing of different specifications of the tire blanks, the weighing accuracy is 0.15 kg. The instrument data is collected by means of the DEVICENET bus. The upper computer realizes the communication with PLC (programmable controller) through TCP/IP network port, collects the quality of the bad tire in real time, and drives the PLC to control the action of the equipment in case of abnormality. The equipment is constantly debugged to meet the needs of the actual application of the site.

2 weighing control process

Adopt highly reliable PLC control system to realize the collection and control of bad tire quality, after calibration of quality standard specification, transform the current PLC control system, driving device and weighing control system, and at the same time establish the communication with the upper computer to realize the real-time collection of weighing data and the determination of quality standard. Alarm and control equipment to continue to act on the tire blanks that do not meet the quality standards. At the same time, the operator is prompted to contact the technician for individual processing, and the current equipment parameters are corrected after processing. The dosing machine automatically collects the data and analyzes it. The normal distribution function analysis method is widely used in the field of tire quality control, using the normal distribution can easily determine the probability of its value occurring in any specified range. Measurement errors in weighing are also generally subject to normal distribution, using this feature, error analysis and quality control can be carried out.

3 Principle of normal analysis and process capability index calculation

Based on the analysis of bad tire quality samples, the use of normal distribution algorithms can achieve the analysis and prediction of data to continuously optimize the tire production process, improve standards, and provide reference data for process improvement. Normal distribution has the following characteristics.

(1) Normal distribution with the mean value as the center, left and right symmetrical value, theoretically no boundary, away from the farther the function value is closer to zero, but will not be equal to zero.

(2) normal distribution, the area under the curve is concentrated in the part of the center of the value of the claim, the farther away from the center, the closer the curve is to the axis, the smaller the area under the curve, beyond a certain range outside the area (probability) can be ignored.

(3) The normal distribution is centered on the mean value, symmetrical left and right, and the normal curve is highest at the mean above the horizontal axis.

(4) In order to facilitate the application, often the normal distribution of variables for the following variable transformations, for the standard normal variable or standard normal deviation, position (i.e., mean) parameter, for the variance (standard deviation) parameter. The transformation transforms the original normal distribution into a standard normal distribution.

(5) Normal distribution determines the offset position of the distribution curve on the horizontal axis. At a certain point, increasing, the curve moves to the right along the horizontal axis; conversely decreasing, the curve moves to the left along the horizontal axis.

(6) The area distribution under the normal curve has a certain pattern, that is, all the normal distribution curves have the same area within the range of standard deviations of the same multiple on the left and right.

(7) Based on the normal distribution through the sample calculation corresponds to the test process index. Through the analysis of the process capability index and historical data comparison can find the current product control process should be improved.

4 Software Architecture Functions

The feeding system can realize the collection, statistics and analysis of quality information. Through the analysis of data, the causes of deviation can be predicted, and according to different causes, corresponding local measures or systematic measures can be formulated to avoid them.

4.1 Quality standard management

Maintain the quality standard of tire blanks, and carry out unified and standardized management of the upper limit and lower limit of the standard quality standard for each kind of tire blank.

4.2 Equipment parameter management

Maintain the specific parameters of the equipment, and configure the baud rate, serial port, data bit, parity bit, P address, and PLC communication parameters for scale communication.

4.3 Shift management

Management of personnel shift management information, recording personnel, shifts, shifts and positions, corresponding to the machine and date. Corresponding shift information is associated with the weighing of bad tires, and a traceability relationship is established, which can be traced back to the shift information and weighing information according to the barcode of the tire blanks. It can analyze the passing rate of weighing from different dimensions of personnel, shift, group, position, date and machine.

4.4 Quality Acquisition

PLC communicates with weighing instrument to collect data into PLC, which communicates with upper computer to collect quality in real time and save it in database.

4.5 Quality deviation alarm

After the upper computer collects the quality of the tire blank, it automatically downloads the quality standard and corresponds to it, alarms those who do not meet the standard, controls the equipment to continue to act, reminds the operator to deal with it, and after dealing with the abnormality, it will start and continue to produce.

4.6 Tire blank quality pass rate

The analysis of the date, machine, shift and team to analyze the rate of bad tire qualification, to provide data support for the rational arrangement of production planning and improvement of process technology.

4.7 Tire blank quality normal distribution

For the date, machine, shift, shift selected sample type, quality normal distribution analysis, find out the reasons for deviation, and take measures to improve, in order to improve the quality of process control.

4.8 Tire blank quality analysis

For the date, machine, material, shift and shift for quality analysis, according to the results of the analysis, to determine the influence of the process performance of the deterioration factors, and optimization and improvement, in order to improve the performance indicators.

4.9 Tire blank quality report analysis

Based on the analysis of weighing data by date, machine, material, shift and group, it can display real-time weighing detail report, weighing abnormality report, abnormality processing report, average value analysis report, extreme value analysis report, pass rate analysis report and failure rate analysis report, which can provide the best data for optimizing production scheduling and improving process.

Conclusion

Tire bad automatic dosing system integrating automatic weighing, automatic control and information technology can automatically collect the quality data of tire blanks, automatically download the quality standard according to the parameters of tire specifications, and alarm and control the defective products in order to improve the product qualification rate. The system is seamlessly integrated with the factory information system and can realize information sharing. The system can improve the quality of tire products, thus increasing the economic benefits of enterprises and the social benefits of the tire industry. The system has been applied in the actual field of many enterprises, and can accurately find and avoid defective products with unqualified quality, missing parts and wrong materials, which plays a significant role in optimizing production scheduling, improving processes and guaranteeing the quality of tires.