Tiara Anugerah (1), Rusindiyanto Rusindiyanto (2)
General Background: Production inefficiency remains a major concern in manufacturing because waste can increase process duration, resource use, and operational costs. Specific Background: PT XYZ, a cosmetic manufacturing company producing hair coloring shampoo, experienced production waste involving high waiting time, repetitive activities, unnecessary inventory, overproduction, product defects, excessive transportation, unnecessary motion, and overprocessing. Knowledge Gap: Previous lean manufacturing studies have commonly emphasized Value Stream Mapping, while limited work has combined process mapping with deeper root cause analysis in the cosmetics sector. Aims: This study aimed to analyze waste in the hair coloring shampoo production process using lean manufacturing, Value Stream Mapping, VALSAT, Process Activity Mapping, fishbone diagrams, and 5 Whys Analysis. Results: The initial production process had a total lead time of 897 minutes and a Process Cycle Efficiency value of 28.09%. The dominant wastes were overproduction with a score of 3, unnecessary inventory with a score of 3, and waiting with a score of 2.33. After proposed improvements, total lead time decreased to 673 minutes, while Process Cycle Efficiency increased to 37.44%. Non-value-added and necessary but non-value-added activities decreased by 57.95% and 18.64%, respectively. Novelty: This study integrates Value Stream Mapping with fishbone diagrams and 5 Whys Analysis to diagnose waste sources in cosmetic product manufacturing. Implications: The findings support better scheduling, quality control coordination, procedure simplification, inventory control, ergonomic layout design, and regular 5S implementation.
Highlights:
Keywords: Lean Manufacturing, Process Cycle Efficiency, Root Cause Analysis, Value Stream Mapping, Waste
The production process is a series of activities in the manufacturing industry aimed at transforming raw materials into finished products through interconnected stages. The cosmetic industry is one of the most important and rapidly growing sectors in the global economy, with cosmetic products becoming part of daily necessities for both men and women [1]. In the production process, companies generally still experience waste [2]. Waste refers to the loss of resources such as materials, time, and capital caused by activities that do not provide added value to the final product. Therefore, waste must be minimized or eliminated because it can reduce productivity and negatively affect the company’s profitability [3].
The company under study is a manufacturing firm engaged in the cosmetic industry, focusing on the development and production of hair care products. One of the products produced is hair coloring shampoo. In its production process, the company still encounters several issues indicating the presence of waste. These conditions are reflected in activities that potentially generate waste, such as product defects, inventory accumulation, and discrepancies between production quantities and sales levels. This situation indicates inefficiencies within the production flow. Such waste has an impact on increased production lead time, additional rework activities, and suboptimal use of resources, including operator working time, raw materials, and machine capacity. Furthermore, the significant amount of product flaws leads to higher manufacturing expenses and lowers the efficiency and effectiveness of the production workflow.
While earlier research has covered the use of lean manufacturing for minimizing waste, a majority of these studies mainly emphasize process mapping through Value Stream Mapping (VSM) without the backing of thorough root cause analysis, especially within the cosmetics sector. This suggests a gap in research that calls for a more extensive approach suited to the specific circumstances of businesses. Based on these problems, this study aims to analyze waste in the production process flow using a lean manufacturing approach. The main objective of lean manufacturing is to eliminate waste or non-value-added activities within a process so that activities throughout the value stream are able to generate value-added outcomes [4]. This concept is used to reduce waste by categorizing activities into value-added, non-value-added, and necessary but non-value-added activities, utilizing the Value Stream Mapping (VSM) tool [5]. VSM is considered an effective method for identifying waste and demonstrating process improvement opportunities within a company’s production system [6].
Furthermore, to identify the root causes of waste, this study also applies Root Cause Analysis (RCA) using a cause-and-effect (fishbone) diagram and the 5 Whys method. Root Cause Analysis (RCA) is a structured approach used to identify the contributing factors behind one or more problems in order to improve organizational performance. In order to conduct more focused corrective actions, the fishbone diagram is used to identify the variables causing defects, including aspects relating to labor, machinery, processes, materials, and the work environment [7]. In addition, the 5 Whys method is used to facilitate a deeper investigation of the root causes by repeatedly asking “why” continuously until the core reason of the issue is found, the 5 Whys method helps to allow a deeper analysis of the main issues [8]. This approach's simplicity stems from the fact that it doesn't require sophisticated supporting tools, which makes it simple to apply by different parties in problem-solving processes and capable of promoting critical thinking and team discussions to swiftly discover core issues [9]. Through the implementation of VSM and root cause analysis, this research is expected to reduce waste in the production process and provide appropriate improvement recommendations to enhance the company’s operational performance.
Data processing was conducted to analyze waste in the production process flow of hair coloring shampoo products at PT XYZ based on production activity data, process times, and the causes of waste occurring during the production process. The method used in this study was lean manufacturing with the Value Stream Mapping (VSM) approach to identify value-added and non-value-added activities within the production flow. In addition, root cause analysis was carried out using Root Cause Analysis (RCA) supported by fishbone diagrams and the 5 Whys Analysis method as the basis for developing improvement recommendations. The stages carried out in this research are explained as follows:
1. Data Collection
The data collection stage was conducted to obtain the information required in this study. The data used were primary data obtained directly through observations and interviews in the production area of PT Aestika Marwa Indonesia. The collected data consisted of production process flow data and production process time data. Production process flow data were used to determine the sequence of activities as well as the flow of materials and information during the production process, starting from raw material receiving to finished products. Meanwhile, production process time data were obtained by observing and recording the time required for each production activity, which was used as the basis for calculating production lead time and Process Cycle Efficiency (PCE).
2. Current State Value Stream Mapping Analysis
At this stage, Current State Value Stream Mapping was developed to describe the initial condition of the production process flow based on activity and production time data. Current State VSM was used to identify value-added and non-value-added activities and to determine the actual condition of the production process. Furthermore, Process Cycle Efficiency (PCE) was calculated. Process Cycle Efficiency (PCE) is a comparison between value-added activities and total lead time. A process can be categorized as lean if the PCE value is greater than 30% using the following formula [10]:
(1)
3. VALSAT Weighting Score
VALSAT weighting score was carried out to determine the types of waste that had the greatest influence on the production process. The waste weight values were obtained from questionnaire data completed by respondents, which were then calculated and classified into each type of waste.
4. VALSAT Score Calculation
Value Stream Analysis Tools (VALSAT) is a tool used to understand the flow of materials and information throughout the production process by identifying the seven types of waste. In the VALSAT method, each waste type is assigned a weight value. The waste weights are multiplied by correlation values consisting of ordinal scales categorized as low, medium, and high, with multiplier values of 1, 3, and 9, respectively [11].
VALSAT Tool Score = Waste Weight × Correlation Value (H, L, M)(2)
Information:
Waste Weight = Waste weight value obtained from questionnaire calculation results
Correlation Value =H (High Correlation and Usefullness) = 9
M (Medium Correlation and Usefullness) = 3
L (Low Correlation and Usefullness) = 1
5. Selected VALSAT T ools Analysis
At this stage, analysis was carried out using the VALSAT tool with the highest score. The selected tool was used to identify production activities categorized as Value Added (VA), Non-Value Added (NVA), and Necessary but Non-Value Added (NNVA).
6. Fishbone Diagram
This stage was conducted to identify the factors causing waste using a fishbone diagram. The analysis considered several aspects, including man, machine, method, material, environment, and measurement.
7. 5 Whys Analysis
The 5 Whys method was used to investigate the root causes of waste more deeply by repeatedly asking “why” until the main cause of the waste was identified.
8. Development of Future State Value Stream Mapping
This stage involved developing Future State Value Stream Mapping to describe the condition of the production process flow after the implementation of improvement recommendations. Future State Mapping represents the Value Stream Mapping condition after improvements have been implemented. The improvements refer to the application of the proposed recommendations and the recalculation of Process Cycle Efficiency (PCE) values [12].
The production activity time data were obtained through direct observation of each production process activity. The data include the processing time required at each workstation and are used as the basis for analyzing production lead time and identifying waste in the production flow, as shown in Table 1.
The current state value stream mapping of the production process can be seen in Figure 1.
Figure 1. Current State Value Stream Mapping
The production process has a total lead time of 897 minutes, with a value-added time of 252 minutes. The Process Cycle Efficiency (PCE) is calculated as follows:
PCE = 100%
PCE = 100% = 28,09%
The weighting of waste is conducted to identify the types of waste that have the greatest impact on the production process. The waste weights are obtained from questionnaire data completed by respondents, which are then calculated and classified into each type of waste. The recapitulation of waste weights is presented in Table 2.
Based on the calculated waste weights, an analysis is conducted for each type of waste occurring in the production process. These weights indicate the contribution level of each type of waste to the overall inefficiency within the production system.
The data is then processed by multiplying the waste weights by the values in each column of the VALSAT matrix once the weight of each type of waste has been determined. The results of the VALSAT score calculation are presented in Table 3.
The following formula is used to determine the VALSAT score after the weight of each type of waste has been obtained:
VALSAT Tool Score = Waste Weight × Correlation Value
The correlation values are defined as follows: High (H) = 9, Medium (M) = 3, and Low (L) = 1. Based on the computation results, Process Activity Mapping (PAM) has the highest score, with a total value of 67.3.
The Process Activity Mapping (PAM) method focuses on identifying and reducing non-value-added activities in the production process through elimination, simplification, or improvement of workflow. The mapping results are summarized in Table 4.
Figure 2. Percentage of Time and Frequency by Activity Type
The comparison of the percentage of time and frequency by activity type is illustrated in Figure 3.
Figure 3. Percentage of Time and Frequency by Activity Type
The fishbone diagram for overproduction waste is presented in Figure 4.
Figure 4. Fishbone Diagram Waste of Over Production
Figure 5. Fishbone Diagram Waste of Unnecessary Inventory
Figure 6. Fishbone Diagram Waste of Unnecessary Motion
Figure 7. Fishbone Diagram Waste of Defect
Figure 8. Fishbone Diagram Waste of Excessive Transportation
Figure 9. Fishbone Diagram Waste of Over Processing
Based on the identified wastes from the previous stage, a 5 Whys Analysis is conducted to determine the root causes of each problem occurring in the production process. This analysis is performed by repeatedly asking “why” in a step-by-step manner until the fundamental cause of the waste is identified. The results of the 5 Whys Analysis are presented in Table 7.
The adjustment of production activity time after the implementation of improvement recommendations is shown in Table 9.
Figure 10. Future State Value Stream Mapping
To assess the performance of the production process after improvement, the Process Cycle Efficiency (PCE) is calculated as follows:
PCE = 100% = 37,44%
The calculation results show that the Process Cycle Efficiency (PCE) increased from 28.09% in the current state condition to 37.44% after the implementation of the proposed improvements.
This study demonstrates that the implementation of the lean manufacturing approach was effective in identifying and reducing waste within the hair coloring shampoo production process at PT XYZ. The analysis results indicate that the most dominant wastes were overproduction (score 3), unnecessary inventory (score 3), and waiting (score 2.3). These wastes contributed to inefficiencies in the production flow, increased production lead time, and accumulation of work-in-process and finished goods. Value Stream Mapping (VSM), Process Activity Mapping (PAM), VALSAT, and Root Cause Analysis (RCA) were used to successfully identify non-value-added activities and the root causes of waste occurring throughout the production process.
With a Process Cycle Efficiency (PCE) rating of 28.09% and an initial production lead time of 897 minutes, the Process Activity Mapping (PAM) analysis revealed that the manufacturing process had not yet reached ideal efficiency. Following the suggested changes, the PCE value rose to 37.44% and the manufacturing lead time dropped to 673 minutes. Value-Added (VA) activities did not change, whereas Non-Value-Added (NVA) and Necessary but Non-Value-Added (NNVA) activities dropped by 57.95% and 18.64%, respectively. Therefore, the lean manufacturing approach can be considered effective in reducing waste and improving operational performance in the production process at PT XYZ.
These results show that the proposed improvements successfully improved production flow efficiency by reducing non-value-added activities and minimizing production delays. The proposed improvement actions focused on improving inter-process scheduling, strengthening coordination between production and quality control, simplifying operational procedures, reducing rework, optimizing inventory management, and applying ergonomic work design and 5S principles. Further research is recommended to evaluate the long-term effectiveness of the proposed improvements and support continuous improvement in production system performance.
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