Problem-solving step analysis for increasing tire static balance levels: a case study

Abstract

One of the company's efforts in implementing the commitment to customer satisfaction is carried out through continuous improvement activities. All indicators are evaluated to determine the level of quality stability against process variations that will impact non-compliance with predetermined product specifications. One of the quality problems found in the tire manufacture industry is the out-percentage of tire uniformity, which suddenly increases, one of which is the value of static balance. This study analyses the process variation factors that occur to take corrective and preventive actions through a series of Root Cause Analysis (RCA), Fault Tree Analysis (FTA), and Failure Mode and Effect Analysis (FMEA). Refers to the analysis result, it was found that there was a problem with the rubber film gauge variation at the manufacturing step of the steel breaker, one of the material components in the tire construction. Two main factors cause rubber film thickness variation: rubber sticky with roll calendar, Radial Run Out (RRO) Roll Calendar out standard, and viscosity compound variation with 12 root problems found. The results of the improvements that have been made can effectively improve rubber film thickness variation, increase the Cpk level of steel breaker material from 0.82 to 1.91 and reduce the out percentage ratio of static balance by 54.65%.

Design and implementation of intelligent electronic component inspection based on PLC and vision system

“…In line with previous research, getting optimal image results does not take a long time (a single minute) because the sensor setup is facilitated by autofocus and auto-brightness, without some experimenting with distance settings and lighting settings [28]. With the ease of setting the vision camera, it can provide added value to the company so that the product change-over process will be faster and more efficient [29], [30]. Initialization of the product according to the specifications is done by observing a vision camera to get the optimum threshold value.…”

Analysis and Defect Improvement Using FTA, FMEA, and MLR Through DMAIC Phase: Case Study in Mixing Process Tire Manufacturing Industry

“…Next, identify the sources and root causes of quality problems and prepare countermeasures and priorities that need to be addressed, starting with the highest priority. FMEA also documents the current condition, risk of failure, and continuous improvement [13]. FMEA is divided into two types, namely Design FMEA and Process FMEA.…”

“…Continuous improvement using the DMAIC cycle is also applied to the Tire and Rubber sector. Several researchers documented the results of their research, the increase in excellent process capability [11][12][13], and a significant decrease in the defect rate [14,15]. Not only in the quality scope, but DMAIC is also able to increase productivity [16] with the Overall Equipment Effectiveness (OEE) indicator increasing from 87% to 92.3% [8,16], and a significant annual saving quality expense [17,18].…”

Terminals and Connector Inspection Innovation using Machine Vision

“…Maintaining product quality levels and identifying types of product defects that require improvement are the objectives of quality control in manufacturing departments. A wide variety of macroscopic, visible, and complex product defects using conventional inspection methods are commonly used, time-consuming, and subjective [3]- [6]. Detecting product defects and classifying product defect types is the goal of automated visual detection.…”