Statistical Process Control (SPC) and Fuzzy-Failure Mode and Effect Analysis (F-FMEA) Approaches to Reduce Reject Products in Wine Bottle Rack Production Process at PT Alis Jaya Ciptatama

PT Alis Jaya Ciptatama (AJC) is a company engaged in the furniture industry, where the products are exported. One of the products from PT AJC is a wine bottle rack. In the production of wine bottle racks at PT AJC, many product defects were found. Therefore, it is necessary to conduct further research to determine the quality of the product, so that the correct product quality improvement is obtained. The purpose of this study was to determine the limits of statistical control and the factors causing defects in wine bottle racks so that the quality improvement provided was right on target. The methods used in this research are Statistical Process Control (SPC) and Fuzzy Failure Mode and Effect Analysis (F-FMEA). SPC method is used to determine statistical control limits and factors causing product defects. The F-FMEA method is used to determine the priority of improvement in improving the quality of wine bottle racks. The results of the research related to the statistical control limits of the SPC method were obtained that the defective data were outside the statistical control limits. While the results of research related to the causes of product failure using the SPC method are human, machine, material, environmental, method, and measurement factors. Factors causing product failure were analyzed using the F-FMEA method so that improvement priorities were obtained, namely the lack of experience of workers with an FRPN value of 269.33. Improvements that need to be made by PT AJC include providing training to mill 1 worker and splitting the logs


INTRODUCTION
Furniture products are products that are in demand by the wider community, both at home and abroad. The furniture industry is an industry that manages raw materials or semifinished materials derived from wood, rattan, and other natural materials into a finished product called furniture which has higher added value and benefits (Salim & Munadi, 2017). PT AJC is a manufacturing company engaged in the furniture manufacturing industry. The products produced by PT AJC are export products sent to America. One of the products produced is a wine bottle rack. Based on the results of interviews conducted with the company's quality control staff, PT AJC has a reject rate quality standard of 10% of the total production carried out. PT AJC has a reject rate that exceeds the set target.
The purpose of this study was to determine the limits of statistical control and the factors causing defects in wine bottle racks, so thatthe quality improvement provided was right on target. Based on the background that has been described, this research will conduct quality control using statistical process control and fuzzy FMEA methods. The relationship between the SPC method and fuzzy FMEA is that the SPC method is used to determine whether the reject rejected within the statistical control limits and to determine the cause of the resulting reject in the production process. Meanwhile, the fuzzy FMEA method is used to analyze failures that cause defective products to be produced and provide suggestions for prevention and improvement to improve Analyzing the failure modes that cause defects, finding the biggest production process failure risk, and providing suggestions for improvements for the next production. 5 Lestari 2020 Wiring harness products To improve the quality of the products produced, reduce product failures, and reduce losses borne by PT EDS Manufacturing Indonesia (PEMI To identify damage to the machine and determine the priority of repairs on the machine that must be given immediate treatment.
8 Krisnaningsih 2020 Facial tissue products Identify the types of defects that occur, identify the factors that cause product defects and increase the competitiveness of the tissue company at PT XYZ. 9 Hardiyanti dkk 2021 Leather products To analyze the quality control of leather products whether it is within the control limits and to identify the factors that cause defects that occur. 10 Ezra 2021 Tempe chips product Knowing the process capability, analyzing the factors causing the deviation of the tempe sago chip product and providing suggestions for improvement with the aim of controlling product quality. 11 Sari 2021 X roastery coffee products To find out the description of the ongoing production process, to examine the factors that cause product failure, to know the actions that must be taken to prevent the occurrence of failed products.
The difference between this study and previous research lies in the calculation of the fuzzy FMEA. The use of fuzzy logic in this study is used to weight each failure mode that exists in the production process of mill 1 wine bottle rack products. Calculations using fuzzy logic can minimize the results of the same priority weighting.

METHOD
The reject data contained in this study is the reject data obtained in the mill 1 process.
Mill 1 process is the process of forming wooden boards into rough components of wine bottle rack products. This process is the first component formation process, causing many reject components to be generated. The types of rejects produced in the production of wine bottle rack components include knots, cracks, holes, fibers, bends, colors, pith, wrong measurements, and mildew. Therefore, it is necessary to carry out quality control to reduce losses borne by the company and deliver products according to a predetermined schedule. Quality control can be done by using Statistical Process Control (SPC) and Fuzzy Failure Mode and Effect Analysis (F-FMEA) methods. The study was conducted using a sample with a population of 35 employees. The sample is part of the characteristics and quantities possessed by the population use (Sugiyono, 2018).
Data processing is carried out aiming to find answers to the formulation of the problem that has been made. In this study, product defect data will be processed using the SPC method with the use of 6 quality control tools. Furthermore, questionnaires will be distributed to workers and quality experts in mill 1. The distribution of questionnaires is carried out to weight each value of S, O, and D in each failure mode. The results of the questionnaire obtained were then tested for validity and reliability using the minitab application. If the results of the questionnaire are valid, then the FRPN value will be calculated using Fuzzy FMEA. The calculation of Fuzzy FMEA will result in which deviations need priority improvement. The advantages of Fuzzy FMEA include (1) the possibility of using linguistic values, (2) it can be used for qualitative and quantitative data, and (3) it can take into account the experience and knowledge of experts (Khasha et al., 2013). The use of conventional FMEA has several drawbacks, namely the weighting of interests in the preparation of the RPN can produce the same value (Chanamool & Naenna, 2016). The difference between the RPN in Fuzzy FMEA and the conventional FMEA method lies in the value of the three components in Fuzzy FMEA using fuzzy numbers that pay attention to the weight of the respondent along with the weight assessment based on the respondent (Mansur & Ratnasari, 2015). FRPN gains are displayed on a scale of 0.1-10 in nine categories starting from very low to very high (Supriyadi et al., 2017).
The analysis and discussion stage is an analysis of the results of data processing that has been carried out based on the SPC and Fuzzy FMEA methods. The analysis and discussion include check sheet analysis, histogram analysis, control chart analysis, Pareto diagram analysis, scatter diagram analysis, analysis of causes of defects, and proposed improvements. This step aims to get a complete picture of the research and as a basis for drawing conclusions and suggestions.

RESULT AND DISCUSSION
Data processing in this study was carried out using the Statistical Process Control (SPC) method to determine whether the defective product was still within the statistical control limits or not and to determine the factors causing the rejection of the wine bottle rack product. Furthermore, data analysis and processing will be carried out using fishbone diagrams and the Fuzzy Failure Mode and Effect Analysis (F-FMEA) method in making suggestions for improvements. The use of fuzzy logic in research will produce more accurate results when compared to traditional FMEA (Keskin & Özkan, 2009).

Statistiqal Process Control (SPC)
Statistical process control (SPC) is a process carried out to monitor standards, take measurements, and determine appropriate corrective actions when products or services are being produced (Jay et al., 2016). This study uses 6 tools used in the SPC method, including: a. Check Sheet The initial step in controlling the quality of the wine bottle rack product is to collect production data and defect data into a check sheet. In the Pareto diagram, reject data will be displayed from the largest to the smallest number of rejects. By using the Pareto diagram, the most dominant type of reject can be identified. Pareto reject diagram can be seen in Figure 2: The scatter diagram in this study is used to determine how strong the relationship between two variables is. The two variables are the number of production variables (x) and the number of reject types (y). The results of calculations using Minitab can be seen in the following figure: Figure 3. Scatterplot of crack vs total production This is indicated by the movement from the lower left to the upper right, which means that the higher the number of production, the higher the number of rejects. e. P-Chart The next stage is the creation of a map of the vehicle. The control chart used is the p control chart, where the purpose of using the p control chart is to determine the proportion of deviations that occur in reject products. The reject data will be declared still within the control limits if the reject data is still between the Upper Control Limit (UCL) and Lower Control Limit (LCL). The following is the result of the calculation of the P control chart which can be seen in Figure 4: In Figure 4, it is known that there are still data that are outside the control limit, namely 6 periods. Periods that exceed the upper control limit are week 4, week 12, and week 13. While the periods that are outside the lower control limit are the 1st week, 2nd week, and 7th week. With data that is still outside the statistical control limits, it can be concluded that PT Alis 278 Jaya Ciptatama has problems in the production process. So it is necessary to do an analysis of quality control in order to find the causes of defective products produced in order to improve product quality. f. Fishbone Fishbone diagram is a diagram that is used to analyze what problems exist in a production process and to find out the causes and effects of these problems. In the wine bottle rack production process, there are 9 types of rejects, including cracked rejects, holes, colors, knots, fungus, pith, fibers, bends, and wrong measurements. The following is a fishbone diagram of 9 types of defective wine bottle racks:  By using fishbone diagram analysis, it ca n be seen the factors causing the reject in the wine bottle rack production process.
The following are the factors that cause the rejection of the wine bottle rack production process: 1. Human factor The cause of rejects in the wine bottle rack production process is that there are mill 1 operators who are less focused on work, resulting in parts of the wine bottle rack being rejected. In addition to this, the lack of accuracy and haste in working due to being chased by targets also has an impact on the occurrence of rejects for wine bottle rack parts.

Method Factor
The cause of the reject was due to an error in the arrangement of the wooden boards in the storage section, causing the wooden boards to become moldy and bent. Rejects in mill 1 were also caused by drying the wood planks directly under the sun, thus causing color rejection on the wood planks.

Engine Factor
The cause of rejects is due to the setting of the machine clamping the board that is too strong, causing the wooden boards to crack and the old age of the machine causing the machine to experience a decrease in machine reliability in the mill 1 process.

Material Factor
The cause of the reject is the quality of the wooden boards that are not good so that many wooden boards have rejects due to the absence of selection of wooden boards.

Environmental factor
The cause of rejects is that a humid environment can cause mold to grow on wooden boards, which can cause black spots on the wooden boards. In addition to humid temperatures, a hot environment can also cause wooden planks to shrink, so an environment with the right room temperature is needed.

Measurement Factor
The cause of the reject is the uncontrolled temperature measurement on the kiln machine. This is due to the absence of control over the temperature of the kiln machine.

Fuzzy Failure Mode and Effect Analysis (F-FMEA)
FMEA is an analysis which, if done correctly and at the right time, will yield great results in assisting engineers in the decisionmaking process during design and development (Leitch, 1995). The FMEA method begins with analyzing the evaluation results in order to identify possible problems that occur based on historical data, consumer complaints, and other supporting data (Walser, 2012). Based on the results of the causal factor analysis using a fishbone diagram related to the rejects produced in the wine bottle rack production process, then an analysis of the FRPN calculation is carried out on each causative factor based on the fishbone diagram. The following are the steps taken to obtain the Fuzzy RPN value. a. Fuzzy Value Input In the fuzzy input stage, the data used is the value of each severity, occurrence, and detection. Fuzzy logic input can be seen in Table 2.  Table  4.14, the membership of the fuzzy values is inputted for each of the existing S, O, and D values. the following is a fuzzy membership function which can be seen in Table 3. O D P1 7 8 9 7 8 9 2 3 4 P2 7 8 9 7 8 9 3 4 5 P3 5 6 7 7 8 9 3 4 5 P4 5 6 7 7 8 9 2 3 4 P5 7 8 9 7 8 9 2 3 4 P6 5 6 7 7 8 9 2 3 4 P7 7 8 9 7 8 9 3 4 5 P8 7 8 9 7 8 9 3 4 5 P9 5 6 7 7 8 9 2 3 4 P10 5 6 7 7 8 9 3 4 5 P11 7 8 9 7 8 9 3 4 5 P12 6 7 8 7 8 9 2 3 4 P13 7 8 9 7 8 9 2 3 4 P14 7 8 9 7 8 9 2 3 4 P15 5 6 7 7 8 9 3 4 5 P16 5 6 7 7 8 9 3 4 5 c. Defuzzyfication The next step is to calculate S, O, and D to get the FRPN value from each predetermined failure mode. FRPN results are obtained from the multiplication of each fuzzy number from S, O, and The following is an example of FRPN calculation.

CONCLUSION
Based on the results of data processing and analysis in this final project, the following conclusions can be drawn: a. It is known that the production of wine bottle racks has 9 types of defects, namely cracks, holes, color, fibers, bends, knots, fungus, wrong measurements, and pith which are still out of control with 13 periods. The data has a value of UCL = 0.199 and LCL = 0.1306 so that a revision is carried out by eliminating data that are outside the control limits with the results of 7 periods being within the statistical control limits. b. Factors that cause reject products at PT AJC are poor quality wood, there are boards that are not in accordance with the predetermined MC standards, workers who are less focused, workers who do not check the quality of wooden boards, there are wooden boards that have a surface the wood is not good, the fibers on the wooden planks are not good, the workers do not change blades regularly, the use of young wood, the inexperienced workers, the occurrence of errors in the process of splitting the logs, the pressure fro m the clamping of the boards is too strong, and the lack of control on the clin machine. c. Based on data processing using the SPC and Fuzzy FMEA methods, it was found that the priority improvement proposals for reject products were obtained, among others by providing training to workers, controlling the temperature on the kiln machine periodically, and selecting wooden boards before entering the mill 1 process. Based on the research conducted, the advice given to PT Alis Jaya Ciptatama is to conduct training for log splitting operators, to add a wood board QC process and to carry out temperature control on the kiln machine. Then, for research that will be carried out in the future, it can be done by integrating the Fuzzy FMEA method with AHP. The AHP method can be used to consider better decisions in determining proposed improvements to existing problems at PT Alis Jaya Ciptatama.