Rationale
The rising demand for automobiles, particularly in large cities and developed economies, has led to an increased need for automotive components for manufacturing, repair, and maintenance (Williamson, 2006) The Global Automotive Component Market Report indicates that this demand will continue to grow due to the expanding automotive market and the establishment of automotive industrial zones globally (Chiarini, 2015) As customers seek a wider variety of high-quality products delivered promptly, manufacturing firms are compelled to enhance their production and delivery processes to maintain competitiveness Consequently, companies like Bosch face ongoing pressure to improve operational performance in a highly competitive landscape.
As a top supplier of automotive components, the company is dedicated to enhancing its production lines by boosting manufacturing efficiency to satisfy customer needs This article focuses on the theme of "Increasing Output by Improving OEE in an Automotive Component Production Line," with the goal of optimizing Overall Equipment Effectiveness (OEE) to elevate output levels and better meet customer demand.
Objective
As stated above, this study applies the DMAIC method to improve the OEE of production lines, increasing output and meeting customer needs
The specific objectives of this thesis are:
1 Review theories related to OEE and DMAIC improvement tool
2 Analysis of the current situation of the production line to define the bottleneck
3 Improve OEE by applying the DMAIC method to solve the problem that happens at the bottleneck
Scope and object
* Space: MSE1 Department of Bosch Vietnam Co., Ltd Long Thanh Industrial Park, Tam An Commune, Long Thanh District, Dong Nai Province, Vietnam
* Time: The study was conducted over a period of 3 months, from January 2023 to March 2023
* Object: The Element production line 04 in MSE1 department at the Bosch Vietnam Co., Ltd
Research methodology
The research employed both qualitative and quantitative methods to investigate issues affecting the production process and the Overall Equipment Effectiveness (OEE) index Qualitative methods, including focus group discussions, were utilized to gather insights from operators, engineers, and production experts, providing a comprehensive understanding of the production line's current challenges In contrast, quantitative methods were applied to measure the impact of these production problems on the OEE index, using statistical techniques to analyze data and propose effective improvement solutions.
Integrating qualitative and quantitative research methods in the analysis of enhancing output through the OEE index of the production line ensures both accuracy and feasibility of the findings Qualitative research provides insights into the current conditions of the production line, while quantitative research assesses the influence of various production factors on the OEE index and suggests potential improvement strategies.
Structure of the report
The expected structure of the thesis includes four main chapters and a conclusion section
• Chapter 1: Introduction to Bosch Vietnam Co., Ltd
• Chapter 3: Reality of an automotive component production line at Bosch Vietnam Co., Ltd
• Chapter 4: Solution to increase output by improving OEE in Automotive component production line
INTRODUCTION TO BOSCH VIETNAM CO., LTD
Overview of Bosch Vietnam Co., Ltd
According to information collected from the website of Bosch Vietnam Co., Ltd
- Bosch Vietnam Co., Ltd is manufacturing with head office at the Ho Chi Minh City plant (HcP) in Dong Nai Province
- Address: Road No 8, Long Thanh Industrial Park, Tam An Commune, Long
Thanh District, Dong Nai Province, Vietnam
Source: https://www.bosch-mobility.com
- Product of Bosch (HcP): Pushbelt
Source: https://www.bosch-mobility.com
Front View leg head ear radius saddle-flank body notch pin head notch pillar body right* left* long saddle shape flank angle roll over leg height
The push belt consists of numerous specially designed steel elements connected along two high-alloy steel loop packs, allowing for adjustments in power by varying the number of loops and the width of the elements This technology is utilized in various hybrid configurations, including micro, mild, and full hybrids, enhancing comfort and fuel economy, exemplified by the dedicated hybrid continuously variable transmission (DH-CVT) Additionally, a multi-speed push belt CVT for electric vehicles enables the downsizing of electronic components while improving efficiency and performance.
Source: MSE1 department of Bosch Vietnam Co., Ltd
Bosch Vietnam Co., Ltd envisions becoming a premier provider of innovative technology and solutions in Vietnam and the ASEAN region The company is committed to sustainable growth by offering high-quality products and services that fulfill customer needs while contributing positively to societal and environmental development.
Bosch is driven by a commitment to create products that are "Invented for life," aiming to inspire enthusiasm, enhance quality of life, and promote the conservation of natural resources The mission statement "We are Bosch" encapsulates the company's core values, strengths, and strategic direction.
Bosch Vietnam Co., Ltd is guided by core values that shape its culture, behavior, and decision-making These core values are:
Customer focus: The company puts the needs and expectations of its customers at the center of everything it does, striving to exceed their expectations and deliver value to them
Innovation: Bosch Vietnam Co., Ltd encourages innovation and creativity, continuously seeking new and better ways to improve its products, services, and processes
Sustainability: The company is committed to sustainability and takes responsibility for minimizing its environmental impact and contributing to the sustainable development of society
Teamwork and respect: Bosch Vietnam Co., Ltd fosters a culture of collaboration and respect, recognizing that diversity and teamwork are essential to achieving its goals and objectives
The company upholds the highest standards of integrity and ethics, ensuring accountability for its actions and decisions while fostering trust among customers, employees, and stakeholders.
Bosch is dedicated to being a responsible and innovative company that prioritizes customer focus, upholding the highest standards of integrity and ethics, while actively contributing to the sustainable development of Vietnam and the ASEAN region.
Bosch Vietnam Co., Ltd faces significant competition in the Vietnamese automotive industry from several key players Major competitors include various multinational and local companies that challenge Bosch's market presence and innovation.
Denso Vietnam: Denso is a Japanese company that produces automotive components such as air conditioning, fuel injection, and electrical systems
NGK Spark Plug Vietnam: NGK is a Japanese company specializing in producing spark plugs for automotive and other applications
Delphi Vietnam: Delphi is an American company that produces a wide range of automotive products, including powertrain systems, fuel injection systems, and electrical systems
Lear Corporation Vietnam: Lear is an American company that produces automotive seating systems, electrical distribution systems, and other interior components for motor vehicles
Continental Vietnam: Continental is a German company that produces various automotive products, including powertrain systems, chassis components, and interior electronics
Bosch Vietnam Co., Ltd faces competition from various companies in the Vietnamese market, especially within the automotive sector Nevertheless, its commitment to innovation, quality, and customer satisfaction has solidified its status as a top supplier of automotive components and other products in the region.
Company history and development
Bosch Vietnam Co., Ltd, a subsidiary of the renowned Bosch Group, is part of a leading multinational engineering and technology company headquartered in Germany This article provides a concise overview of the history and development of Bosch Vietnam Co., Ltd.
2008: Bosch Vietnam Co., Ltd was established in Ho Chi Minh City, Vietnam, to provide sales and marketing support for Bosch products
2009: Bosch Vietnam Co., Ltd opened its first manufacturing plant in the Amata Industrial Zone in Dong Nai Province, producing automotive products such as spark plugs and wiper blades
2011: Bosch Vietnam Co., Ltd expanded its manufacturing operations to include power tools, security systems, and industrial technology products
2013: The company opened a new manufacturing plant in Long Thanh, Dong Nai Province, which became its primary manufacturing facility in Vietnam
2014: Bosch Vietnam Co., Ltd established the Automotive R&D Center in Ho Chi Minh City, focused on developing advanced automotive technologies and solutions for the ASEAN region
2017: The company opened a new software and engineering center in Ho Chi Minh City, focused on developing innovative software solutions for Bosch products
In 2020, Bosch Vietnam Co., Ltd marked its 10th anniversary, highlighting a decade of success in providing high-quality products and services to customers in Vietnam and the ASEAN region.
Since its inception in 2008, Bosch Vietnam Co., Ltd has seen remarkable growth, enhancing its manufacturing capabilities and setting up research and development centers in Vietnam to create innovative technologies and solutions for regional customers.
Organization chart of the company
- HcP/PT: Technical Plant Manager who responsible for the operations of the Manufacture
- HcP/MSE1: Department responsible for producing Element – component of Pushbelt
- HcP/MSE2: Department responsible for producing Loop – component of Pushbelt
HcP/MSE1 HcP/MSE2 HcP/MSE3 HcP/TEF HcP/BPS HcP/HSE PS/QMM-
- HcP/MSE3: Department responsible for assembling components to make a complete Pushbelt
- HcP/TEF: Department responsible for repairing the machine or equipment when having the problem
- HcP/BPS: Department responsible for the activity of Bosch Production System
- HcP/HSE: Department responsible for environment health safety
- PS/QMM-HcP: Department responsible for checking the quality of product
Field of activity
Industry classification: Manufacture of other parts and accessories for motor vehicles.
Summary
In this chapter, the author presents Bosch, a global leader in the automotive market with decades of experience, emphasizing its commitment to customer benefits Bosch's strategy focuses on continuously enhancing quality to meet customer needs The thesis titled “Increase Output by Improving OEE in an Automotive Component Production Line: A Case of Bosch Vietnam” aligns perfectly with the company's strategic goals and requirements.
LITERATURE REVIEW
OEE definition
Overall Equipment Effectiveness (OEE) is a key metric that assesses the performance of equipment by evaluating how effectively it fulfills its intended purpose This concept is extensively utilized across different industries, particularly in manufacturing, to pinpoint opportunities for enhancing production processes.
OEE is calculated by multiplying three factors: Availability, Performance, and Quality These factors are defined as follows (Nakajima, 1988):
Availability refers to the percentage of time that equipment is operational and ready for production It takes into account unplanned downtime from equipment failures, scheduled maintenance, and various other factors that may render the equipment unavailable.
Net operating time is calculated by subtracting unplanned downtime from the planned producing time Performance evaluates the speed and efficiency of equipment during production, taking into account speed losses, startup losses, and other factors that may impact the output rate.
Quality: This measures the percentage of output that meets the required quality standards It considers defects, rework, and scrap that may result from production processes
The formula for calculating OEE is as follows:
Another method to calculate OEE based on output (Abd Rahman, et al., 2020):
Utilizing Overall Equipment Effectiveness (OEE) enables manufacturers to pinpoint inefficiencies in their production processes, facilitating targeted actions to enhance efficiency and minimize waste Furthermore, OEE provides a framework for monitoring performance trends and establishing improvement benchmarks, which ultimately boosts productivity, elevates product quality, and lowers operational costs.
The optimal Overall Equipment Effectiveness (OEE) level typically varies by industry and product type, but manufacturing experts generally agree that a benchmark of 85% or higher is ideal for most businesses.
Achieving an Overall Equipment Effectiveness (OEE) of 85% signifies that the production system is operating efficiently and adhering to industry standards This level of OEE also reflects optimal resource utilization, including labor, materials, and energy, resulting in high operational efficiency.
An OEE below 85% signals potential waste of time, resources, and money in the production process, which can lead to decreased output, compromised product quality, and reduced equipment reliability, ultimately impacting the company's market competitiveness.
Therefore, achieving a minimum OEE level of 85% will help companies achieve higher production efficiency, save resources and production costs, and meet the standards and requirements of customers.
Cycle time definition
The production cycle time, also known as flow time, refers to the duration between two consecutive production units at the conclusion of the production process In contrast, process cycle time indicates the period during which a unit is actively being worked on at any stage of production The formula for calculating cycle time is essential for optimizing production efficiency.
Cycle time = takt time × OEE Reducing the manufacturing cycle time offers several advantages, such as decreased inventory, lower costs, enhanced product quality (as process issues can be
A shorter manufacturing cycle time leads to quicker responses to customer orders and enhanced adaptability, resulting in faster delivery of the initial batch of finished products This efficiency significantly reduces the time-to-market for businesses (Herrmann, J W., & Chincholkar, M M., 2000).
Bottleneck definition
Bottlenecks are critical factors that restrict a plant's maximum capacity (Liu, L., et al., 2023) In "The Goal," Goldratt discusses the Theory of Constraints (TOC), highlighting that a bottleneck is the process that constrains the overall throughput of a system, often identified as the one with the longest cycle time.
While some experts support the traditional definition of a bottleneck, others contend that factors like variability in processing times and limited capacity in upstream processes can also lead to bottlenecks Identifying these constraints necessitates a thorough analysis of the specific system, as there is no universal solution applicable to all scenarios.
Tang H noted in his research that the subsystem with the longest cycle time also exhibits low Overall Equipment Effectiveness (OEE), identifying it as the true bottleneck in the system This insight enhances the understanding and definition of bottlenecks in a more accurate and comprehensive manner.
DMAIC method
DMAIC, which stands for Define, Measure, Analyze, Improve, and Control, is a data-driven life-cycle methodology utilized in Six Sigma projects to enhance process performance This approach is a crucial component of a company's Six Sigma program, as highlighted by M Sokovic, D Pavletic, and K Kern Pipan in 2010.
DMAIC, as outlined by Dang Ngoc Su and Nguyen Dinh Phan (2017), is an enhanced approach to Six Sigma that encompasses five key phases: Define, Measure, Analyze, Improve, and Control This methodology relies on data gathered during the production process to identify and implement strategies aimed at reducing errors and enhancing overall efficiency.
The DMAIC process works well as a breakthrough Companies everywhere adopt this approach because it enables real improvement and real results The method works
13 equally well based on change, cycle time, productivity, and design (Pham Huy Tuan, Nguyen Phi Trung, 2016)
The acronym DMAIC represents the five interlinked phases of the methodology: Define, Measure, Analyze, Improve, and Control
The DMAIC process, which stands for Define, Measure, Analyze, Improve, and Control, is a data-driven quality improvement strategy essential to Six Sigma, as noted by Sarah E Burke & Rachel T Silvestrini (2017) It can also be utilized independently or alongside other methodologies like Lean DMAIC encompasses defining the problem, measuring current performance, analyzing root causes, improving processes through testing solutions, and controlling processes to maintain improvements over time.
Each phase has a distinct purpose and function and can be defined in simplified terms as follows:
The Define stage, as outlined by De Mast and Lokkerbol (2012), is the crucial first phase of the improvement process, where managers establish clear goals post-implementation and identify the problem to be addressed This problem must align with the company's business strategy and meet customer requirements Key steps in the Define stage of DMAIC should be meticulously followed to ensure effective outcomes.
Defining the project scope is the essential first step, as it outlines the necessary changes and objectives to be achieved Following this, it is important to collect information regarding the product or production process that requires improvement, including data on performance, quality, and any existing issues.
Identifying critical factors is essential for enhancing product quality and production performance, as it allows teams to concentrate their efforts on the most significant issues impacting outcomes.
Determine measurement criteria: To evaluate the effectiveness of the improvements, it is essential to determine the measurement criteria to assess the performance of the product or production process
Determine project plan: Finally, the project plan should be determined, including the timeline, budget, essential resources, and activities
In the Define stage of the DMAIC method, essential tools and techniques include Voice of the Customer (VOC) to capture customer needs, Benefit-Effort Analysis for project prioritization, Process Mapping to outline the entire process and define its scope, Pareto Diagrams to identify key issues for prioritization, and Brainstorming to generate ideas for improvement opportunities.
In this thesis, the author uses VOC and the Brainstorming method to define problems needing to improve
The "Voice of the Customer" (VOC) is a crucial method for capturing and analyzing customer feedback, as highlighted by Cooper and Dreher (2010) This process helps identify customer needs, expectations, preferences, and pain points by gathering and interpreting feedback The insights gained from VOC are essential for enhancing the quality and effectiveness of products and services.
The VOC method typically involves multiple steps, including:
Identifying the customers to survey or interview
Designing and conducting surveys or interviews to gather customer feedback Analyzing the feedback to identify patterns, themes, and trends
Prioritizing and categorizing customer needs, expectations, and preferences Developing solutions to address the identified customer needs
The VOC method is applicable across multiple industries, including product development, marketing, customer service, and quality control By leveraging the VOC method, businesses gain valuable insights into customer needs, enabling them to enhance the quality of their products and services.
Brainstorming, as defined by Alex Osborn (2012), is a creative problem-solving technique designed to rapidly generate a multitude of ideas This method encourages free thinking, allowing participants to produce ideas without worrying about their practicality or quality.
A group typically performs the brainstorming technique in a structured and open-minded way The following steps are involved in the brainstorming process
The brainstorming method typically involves a group of people who come together to generate ideas in a structured, yet non-judgmental way The process involves the following steps:
Define the problem or goal: The group should have a clear understanding of the problem they are trying to solve or the goal they are trying to achieve
Set a time limit: The group should agree on a time limit for the brainstorming session, usually between 15 and 30 minutes
Generate ideas: The group should generate as many ideas as possible without evaluating or criticizing them Ideas can be written on a whiteboard or flip chart or recorded electronically
Encourage participation: Everyone in the group should be encouraged to participate and contribute their ideas, even if they seem unconventional or unrealistic
Clarify and expand on ideas: After the brainstorming session, the group should review and clarify the ideas generated, and identify any potential for further development
Evaluate and select ideas: Finally, the group should evaluate the ideas and select the ones that are most promising for further development
Brainstorming is a useful technique for generating new ideas, solving problems, and fostering creativity in a group setting
The Measure phase, as outlined by Shaikh and Kazi (2015), is the second step in the DMAIC methodology, which is a systematic approach for problem-solving and enhancing processes This phase primarily aims to create a baseline for process performance by gathering and analyzing data pertinent to the issue identified during the Define phase.
The Measure phase includes the following steps:
To initiate the Measure phase, it is essential to create a comprehensive data collection plan This plan specifies the types of data to be gathered, the methods of collection, and the individuals responsible for the process By establishing this framework, the accuracy and representativeness of the collected data are ensured.
To effectively address the identified problem, data must be collected according to a predefined plan, ensuring its relevance to the issue at hand This data can be either quantitative or qualitative Following collection, the data is analyzed to uncover patterns, trends, and potential causes of the problem, often utilizing statistical tools to pinpoint areas in need of improvement.
To assess process performance, analyze the data and compare it to the goals set during the Define phase This analysis reveals the gap between current and desired performance levels.
Data analysis is essential for pinpointing the root causes of issues, which are the fundamental factors contributing to the problem Addressing these root causes is crucial in the subsequent phase of the DMAIC methodology.
Previous related research works
No Author Application field Tool Result
Improving OEE of a Beverage Manufacturing Plant Using Lean Six Sigma Methodology
Improved OEE from 52.4% to 72.1% through reduced downtime, improved quality, and increased efficiency
Improving OEE of a Solar Cell Production Line Using
Improved OEE from 42.5% to 61.2% through reduced downtime, improved equipment reliability, and increased efficiency
Improving OEE in a Manufacturing Company Using Kaizen
Improved OEE from 46.5% to 67.8% through reduced downtime, improved quality, and increased efficiency
Improving OEE in a Food Processing Plant Using Lean Manufacturing Tools
Lean manufacturing tools including 5S, visual management, and standardized work
Improved OEE from 54.2% to 78.3% through reduced downtime, improved quality, and increased efficiency
Improving OEE in a Semiconductor Assembly Line Using the Six Sigma DMAIC Methodology
Improved OEE from 73.9% to 81.2% through reduced downtime, improved quality, and increased efficiency
No Author Application field Tool Result
Improving OEE in a Small- Scale Industry Using TPM and VSM
Total Productive Maintenance (TPM) and Value Stream Mapping (VSM)
Improved OEE from 48.7% to 67.2% through reduced downtime, improved equipment reliability, and increased efficiency
Equipment Effectiveness Using Total Productive Maintenance in a Beverage Manufacturing Company
Improved OEE from 50.5% to 70.3% through reduced downtime, improved equipment reliability, and increased efficiency
Improving OEE of a Mining Crushing Plant Using Six Sigma
Six Sigma approach Improved OEE from 47.8% to 65.7% through reduced downtime and increased efficiency
Improving the Overall Equipment Effectiveness of a Manufacturing System Using the Taguchi Loss Function
Improved OEE from 62.8% to 76.7% through reduced downtime, improved quality, and increased efficiency
Improving OEE in the manufacturing industry using the six-sigma approach and Pareto analysis
Six Sigma approach and Pareto analysis
Improved OEE from 47.7% to 75.6% through reduced downtime, improved quality, and increased efficiency
The gap between previous research results and current situation
The productivity of systems can be significantly improved by utilizing OEE, which serves as a crucial KPI (Fuzzy, 2015)
Overall Equipment Effectiveness (OEE) is a crucial metric for assessing performance and enhancing the long-term management of equipment efficiency It focuses on restoring equipment to a near-new state, boosting its performance capabilities, and reducing production losses.
The utilization of OEE metrics is commonly applied in production systems Evaluating this approach can result in better production planning and increased equipment availability (Parida A Kumar U , 2009)
OEE is a systematic method that helps set production goals while utilizing effective management tools and techniques to ensure sustainable availability, optimal performance efficiency, and high-quality rates.
Researchers have adapted the formula for calculating the Overall Equipment Effectiveness (OEE) index to suit different industrial contexts, leading to various concepts such as overall factory effectiveness, overall plant effectiveness, and total equipment effectiveness performance (Muchiri P., et al., 2011) A substantial body of literature exists on OEE and its diverse applications across industries, as detailed in Table 2.1.
Improving the Overall Equipment Effectiveness (OEE) index is essential for sustainable manufacturing in the automotive industry The OEE index provides critical insights into the condition of production line machinery and equipment This study seeks to develop a framework that enhances product performance and boosts productivity in automotive component production lines through the effective use of OEE.
Methodology
Figure 2.3 shown the application flowchart to solve the company's problem
Define Measure Analyse Improve Control
Figure 2 3 Flowchart of thesis methodology
Data collection and data analysis
Identify the classification and the root cause of Loss
Define actions to improve Toploss (Apply PDCA cycle)
Set target and kick off the project
Implement defined corrective actions when issues arise in the process
The PDCA cycle proposed by the author to solve the problems of the Fine Blanking process at the Improve phase is as follows:
1.Feb 5.Feb 10.Feb 15.Feb 20.Feb 25.Feb 30.Feb
Figure 2 4 PDCA cycle Gantt chart
In the define stage, the author evaluates the current market landscape and the company's circumstances to pinpoint imminent challenges This assessment is crucial for establishing the project's focus and identifying areas for enhancement By gaining insights into the company's background, the team can establish clear objectives and initiate the project with a targeted action plan.
Defining the project allows the team to pinpoint critical areas for improvement, enabling the company to tackle its challenges effectively This process includes a comprehensive analysis of the company's current situation and an evaluation of external factors influencing its performance.
Focusing on the root causes of issues and establishing clear objectives enables the team to create a strategy for sustainable improvement The define stage is essential for project success, as it establishes the foundation and direction for the entire team.
In this phase, we will explore the key steps involved in the define stage, including analyzing the company’s background, identifying areas of improvement, setting clear
Establish a plan and timeline for implementing solutions to solve any possible issues, including corrective and preventive actions
Implement defined corrective actions when issues arise in the process
Check if OEE is on target or not
Re-do the actions if the OEE is not stably reached the target and the issues still occur
OEE index is stably reached the target
→ Done Implementing defined preventive actions to minimize the occurrence of issues
To successfully initiate the project, we will establish 30 targets and create a detailed action plan Additionally, we will analyze the responsibilities of each team member and explore best practices to guarantee a positive outcome.
In the measure phase, the author gathers real-time data on factory downtime and its causes, which is essential for the subsequent data analysis This phase is crucial for pinpointing inefficiencies in the manufacturing process and formulating strategies to enhance overall efficiency.
Collecting downtime data requires determining the length and reasons for each stoppage This information is sourced from an online system (SAP) and is directly updated by the operator within that system.
After collecting the data, analyzing it reveals patterns and trends in downtime events By identifying the root causes of these stoppages, strategies can be developed to minimize or eliminate them, ultimately reducing costs and enhancing efficiency.
In the analyze phase, the author examines the data gathered earlier to pinpoint the primary losses and their root causes This stage is essential for formulating effective strategies aimed at minimizing downtime, enhancing efficiency, and boosting overall factory performance.
Data analysis plays a crucial role in identifying the key factors behind losses, including machine breakdowns, operator errors, and raw material shortages By pinpointing these root causes, teams can formulate effective strategies to reduce or eliminate them Conducting a top loss analysis allows for the identification and ranking of the most critical causes of downtime, enabling teams to prioritize their efforts and concentrate on the most impactful areas for improvement.
In this phase, the author examines data analysis methods, focusing on statistical techniques and root cause analysis Additionally, the author and experts share best practices for identifying and mitigating significant losses, emphasizing the use of data visualization tools and collaborative problem-solving strategies.
By the end of the analysis phase, the team will have a comprehensive understanding of the factory's top losses and their root causes, enabling them to develop
31 effective strategies to reduce downtime, increase efficiency, and improve overall factory performance
In the improve phase, the author will implement the previously identified solutions by developing a strategic plan This stage focuses on executing the solutions, evaluating their effectiveness, and making necessary adjustments to enhance overall performance.
The implementation plan will outline clear actions, timelines, and assigned responsibilities to ensure successful execution The team will collaborate effectively, ensuring that all participants comprehend their roles in the process.
The team will diligently track the implementation plan's outcomes, assessing progress and evaluating the effectiveness of the solutions in minimizing top losses Any challenges encountered during the implementation will be swiftly resolved to guarantee the plan's success.
In this phase, the team will focus on best practices for effective solution implementation, emphasizing the importance of clear communication channels, progress monitoring, and prompt issue resolution Additionally, strategies for sustaining improvements will be discussed, including continuous improvement initiatives and employee training programs.
By the conclusion of the improvement phase, the team will effectively implement strategies to minimize top losses and enhance factory performance Furthermore, they will gain a thorough understanding of the effects of their initiatives, empowering them to sustain ongoing improvements and foster future success.
REALITY OF AN AUTOMATIVE COMPONENT PRODUCTION
Current situation at a manufacturing
The global demand for automotive components has surged in recent years, reflected in the annual rise in automobile production and sales In 2021, the International Organization of Motor Vehicle Manufacturers reported that worldwide automobile production reached significant levels, highlighting the industry's growth.
74 million units, an increase of over 4% compared to 2020
The Asia-Pacific region is projected to see a significant increase in demand for automotive components, reaching approximately $394 billion by 2023, according to Grand View Research (2020) This growth is expected to occur at a compound annual growth rate (CAGR) of around 5.1% from 2020 to 2023.
By 2023, North America's demand for automotive components is expected to reach around $327 billion, growing at a compound annual growth rate (CAGR) of approximately 3.9% Additionally, MarketsandMarkets (2021) forecasts that from 2023 to 2028, the automotive component demand in the Asia-Pacific region will increase at an average annual rate of 4.7%, while North America will see a growth rate of 3.3%.
Bosch's primary product, the push belt, is a crucial auto part, and as the demand for automotive components rises, so does Bosch's market presence The company primarily serves customers in the Asia-Pacific and North American markets, where the demand for automotive components continues to grow This increasing customer demand is evident in the comparison of Bosch's customer demand in the first half of 2023 with the same period last year, highlighting a notable percentage difference To ensure a more stable and predictable demand pattern, the logistics department has leveled production accordingly.
Source: Logistics department of Bosch Vietnam Co., Ltd
In the first half of 2023, Bosch experienced a notable increase in customer demand for pushbelts, with demand from March to June surpassing the same period in the previous year April, May, and June marked significant growth, each showing an increase of over 6% Additionally, February 2022, coinciding with Tet celebrations, recorded lower demand compared to January 2023.
A pushbelt is an assembly of Elements and a Loop, so when the demand for a Pushbelt increases, the demand for an Element will increase So, customer demand for MSE1 is rising
In the first half of 2023, customer demand for MSE1, the final product of the manufacturing process, has significantly exceeded the factory's production capacity, as illustrated in the accompanying chart.
Jan Feb Mar Apr May Jun
Figure 3 2 MSE1 Customer’s demand vs Capacity chart
Source: Logistics department of Bosch Vietnam Co., Ltd
In February 2023, customer demand exceeded capacity by 3.23%, with similar trends observed in subsequent months: 2.05% in March, 3.12% in April, 3% in May, and 3.16% in June Without enhancements in production productivity, the company risks failing to meet customer demand, potentially resulting in the loss of loyal customers.
From this background, the company must improve the production line to increase output and meet customers’ demands.
Target capacity
According to Figure 3.2, the plant will face a product shortage for customers from February to June, with the peak shortage reaching 3.23% in February In response, the author and engineers have proposed a 3.23% increase in capacity However, if the demand-capacity gap is less than 3.23% in any month, the company may reduce resource usage by decreasing POT.
Jan.23 Feb.23 Mar.23 Apr.23 May.23 Jun.23
Demand leveling vs Capacity of MSE1
Process flow
Figure 3 3 Process flow to produce the element
Source: MSE1 department of Bosch Vietnam Co., Ltd
The manufacturing process of elements in a plant consists of several key stages It begins with the de-coiling of metal coils, followed by the Fine Blanking process, where the coils are cut into elements and subjected to inspection and measurement The next stage is Hardening, where elements are heat-treated in an oven, quenched in oil, and tempered at a lower temperature Subsequently, the Deburring and Body Grinding processes smooth the edges and remove burrs from the elements After further inspection and measurement using stone, detergent, and water, the elements are stored for mixing code creation Finally, in the Mixing and Washing processes, element lots with similar parameters are combined in a machine and transported via conveyor to a washing machine for thorough cleaning.
Identify bottleneck
To define bottleneck, the author collects data about OEE and cycle time to analyze
Table 3 1 OEE and Cycle time of each process
FB HD DB BG 1-Tub Mixing Washing
Source: MSE1 department of Bosch
Figure 3 4 Cycle time & OEE index in every process
Source: MSE1 department of Bosch Vietnam Co., Ltd
The data indicates that Fine Blanking has the lowest Overall Equipment Effectiveness (OEE) at 77.5% and the longest cycle time of 0.0395 seconds Additionally, the processes following Fine Blanking experience significant delays due to waiting for work-in-progress (WIP), resulting in a reduced actual output capacity.
Therefore, Fine Blanking is the bottleneck of the whole element line 4
FB HD DB BG 1-Tub Mixing Washing m in u te
SOLUTION TO INCREASE OUTPUT BY IMPROVING OEE IN
Result discussion
In March, the Availability index was 82.76% and the Quality index was 97.68%, contributing to an overall OEE index of 80.42% This improvement enhanced the factory's operational capability, resulting in a 3.77% increase in capacity and successfully meeting customer demand.
In months with excess capacity, the factory can reduce POT to help save operational costs
This project has shown that forming a dedicated problem-solving group in response to factory issues leads to effective solutions The factory's main objective is to achieve customer satisfaction, highlighting its commitment to enhancing product and service quality while promoting positive customer interactions.
In summary, the factory has attained positive outcomes in its production process by focusing on Availability, Quality, and Overall Equipment Effectiveness (OEE) Its enhanced capacity to meet customer demands has played a crucial role in its success By forming a focus group to tackle challenges, the factory has shown a strong commitment to customer satisfaction and a clear long-term vision.
The Bosch plant understands that output and Overall Equipment Effectiveness (OEE) are crucial performance indicators Enhancing OEE and output demands a concerted effort from all departments and team members To tackle this challenge, the Bosch team employed the DMAIC (Define, Measure, Analyze, Improve, Control) methodology, adopting a smart and structured approach This process enabled them to pinpoint areas for improvement and devise solutions that successfully enhanced OEE while meeting customer output expectations.
As the author of this thesis, I have gained valuable insights from this experience Enhancing Overall Equipment Effectiveness (OEE) and output is a complex challenge that demands commitment from all team members Implementing the right strategies and methodologies, along with continuous improvements, is essential for success.
The team met its OEE and output goals, yet opportunities for enhancement remain Key areas for improvement involve tackling the top 10 availability and quality challenges, as well as optimizing the balance of production lines with other processes Future research and advancements can leverage the groundwork established by this project to enhance manufacturing processes at Bosch and similar facilities.
A A Abimbola et al (2019) Improving OEE in a Manufacturing Company Using
Abd Rahman, M S., Mohamad, E., and Abdul Rahman, A A (2020) explored the enhancement of overall equipment effectiveness (OEE) through the application of simulation as a decision-making tool for line balancing, as published in the Indonesian Journal of Electrical Engineering and Computer Science, Volume 18.
MarketsandMarkets (2021) Automotive Component Market by Component (Tires,
Battery, Engine Oil, Filters, Brake Systems, Lighting, Spark Plugs), Vehicle (Passenger Car, Commercial Vehicle), Autonomous Driving, EV, Region, and Aftermarket - Global Forecast
Report North America, APAC: Grand View Research (n.d.) Automotive Component
Market Size, Share & Trends Analysis
Basu, R (2004) Implementing Quality – A Practical Guide to Tools and Techniques
Braglia M, Frosolini M, Zammori F (2008) Overall equipment effectiveness of a manufacturing line (OEEML) An integrated approach to assess systems performance International Journal of Manufacturing Technology and Management, 8-29
Chiarini, A (2015) Improvement of OEE performance using a Lean Six Sigma approach: an Italian manufacturing case study International Journal of Productivity and Quality Management, 16(4), 416-433
Cooper, R G., & Dreher, A (2010) Voice-of-customer methods Marketing management, 19(4), 38-43
Dal B, Tugwell P, Greatbanks R (2000) Overall equipment effectiveness as a measure of operational improvement–a practical analysis International Journal of Operations & Production Management, 1488-1502
Dang Ngoc Su, Nguyen Dinh Phan (2017) Quality Management Ha Noi: National
De Mast, J., & Lokkerbol, J (2012) An analysis of the Six Sigma DMAIC method from the perspective of problem solving International Journal of Production Economics, 139(2), 604-614
E K Okeke and S A Okonkwo (2020) Improving Overall Equipment Effectiveness
Using Total Productive Maintenance in a Beverage Manufacturing Company Fuzzy, Z F (2015) Overall Equipment Effectiveness (FOEE): capturing performance fluctuations through LR Fuzzy numbers Production Planning & Control, 451-
G K Arumugam and R Raju (2018) ưImproving OEE in a Small-Scale Industry Using
Ghosh, S., Mandal, M C., and Ray, A (2023) conducted a study on the critical performance parameters of green supply chain management aimed at enhancing sustainability in tea processing companies, utilizing Pareto analysis Their findings were published in the Journal of The Institution of Engineers (India): Series C, volume 104, issue 1.
Goldratt, E M., Cox, J., & Whitford, D (2006) The goal HighBridge
Herrmann, J W., & Chincholkar, M M (2000) Design for production: a tool for reducing manufacturing cycle time In International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 35135
International Organization of Motor Vehicle Manufacturers (OICA) (2022) Retrieved from Production statistics - World and regional production: https://www.oica.net/category/production-statistics/
Liu, L., et al (2023) Research on Production Simulation and Bottleneck Identification for Intelligent Printing Plant Journal of Imaging Science and Technology, 1-7
M J Hadi et al (2021) Improving OEE in a Food Processing Plant Using Lean
M P Gokhale and M K Kale (2018) Improving OEE in the manufacturing industry using the six-sigma approach and Pareto analysis
M R Almeida et al (2019) Improving the Overall Equipment Effectiveness of a
Manufacturing System Using the Taguchi Loss Function
M Sokovic, D Pavletic (2007) Quality improvement - PDCA cycle vs DMAIC and
DFSS Journal of Mechanical Engineering, 369-378
M Sokovic, D Pavletic, K Kern Pipan (2010) Quality improvement methodologies–
PDCA cycle, RADAR matrix, DMAIC and DFSS Journal of achievements in materials and manufacturing engineering, 43(1), 476-483
Mittal, A., Gupta, P., Kumar, V., Al Owad, A., Mahalwat, S., & Singh, S (2023) The performance improvement analysis using Six Sigma DMAIC methodology: A case study on Indian manufacturing company Heliyon
Muchiri P, Pintelon L, Gelders L, Martin H (2011) Development of maintenance function performance measurement framework & indicators International Journal of Production Economics, 295-302
Nakajima, S (1988) Introduction to TPM: total productive maintenance Productivity
O Nyumba, T., Wilson, K., Derrick, C J., & Mukherjee, N (2018) The use of focus group discussion methodology: Insights from two decades of application in conservation Methods in Ecology and evolution, 9(1), 20-32
O Onur et al (2021) Improving OEE of a Mining Crushing Plant Using Six Sigma Osborn, A (2012) Applied imagination-principles and procedures of creative writing
Parida A Kumar U (2009) Maintenance productivity & performance measurement In
Handbook of maintenance management and engineering Springer London, 17-
Pham Huy Tuan, Nguyen Phi Trung (2016) Production and Quality Management course Ho Chi Minh City: Ho Chi Minh City National University
R F Seidel et al (2020) Improving OEE of a Solar Cell Production Line Using Total
R Singh et al (2021) Improving OEE of a Beverage Manufacturing Plant Using Lean
Sarah E Burke & Rachel T Silvestrini (2017) The Certified Quality Engineer
Handbook (4th ed) ASQ Publishing Opportunities
Shaikh, S., & Kazi, J (2015) Review on six sigma (DMAIC) methodology
Tang, H (2019) A new method of bottleneck analysis for manufacturing systems
Thomas McCarty, Michael Bremer, Lorriaine Daniels, Praveen Gupta (2004) The six
- sigma black belt handbook (1th ed) Motorola University
Watson, H A (1962) Fault tree analysis Bell Laboratories, 32
Williamson, R M (2006) Using Overall Equipement Effectiveness: The Metric and theMeasures Strategic Work Systems: Columbus, OH Retrieved June 20, 2006, from www.swspitcrew com
Y C Wang et al (2019) Improving OEE in a Semiconductor Assembly Line Using the
Zammori F, Braglia M, Frosolini M (2011) Stochastic overall equipment effectiveness
International Journal of Production Research, 6469-6490
Loss time and scrap goods recording in January
Monday Tuesday Wednesday Thursday Friday Saturday Sunday Monday Tuesday Wednesday Thursday Friday Saturday Sunday Sunday Monday Tuesday
Code Accumulated 2-Jan 3-Jan 4-Jan 5-Jan 6-Jan 7-Jan 8-Jan 9-Jan 10-Jan 11-Jan 12-Jan 13-Jan 14-Jan 15-Jan 29-Jan 30-Jan 31-Jan
The week progresses with a consistent cycle from Wednesday to Tuesday, highlighting the repetitive nature of daily life Each day brings its own challenges and opportunities, culminating in a sense of loss that resonates throughout the week.
The code accumulation data spans from March 1st to March 31st, detailing the daily accumulation of code throughout the month Each day's entry reflects the total code accumulated, providing insights into the development progress over this period This information is crucial for tracking productivity and identifying trends in coding activity.
+ Sponsor: Thai Hoang Phuc (Team leader of Toolshop-Fine Blanking team works at Bosch)
+ Process Expert: Pham Quang Phu (Toolshop-Fine Blanking engineer works at Bosch),
Le Duy Thanh (Toolshop-Fine Blanking engineer works at Bosch)
+Moderator: Ha Thi Ngoc Anh
+ Place: Meeting room 16 at Bosch Vietnam Co., Ltd
Introduce the motivation/ Background Introduce the current stage of OEE/ A%-Q%-P%
Introduce the target stage of A%-Q% and OEE
+ In your opinion, what is the cause of Tool safety loss
+ In your opinion, what is the cause of Oil leakage loss
+ In your opinion, what is the cause of Clutch overload loss
+ In your opinion, what is the cause of Hydraulic pressure NOK loss
+ In your opinion, what is the cause of Step control loss
Solution discussion and action plan of A
+ What is the solution to solve the Tool safety loss
+ What is the solution to solve the Oil leakage loss
+ What is the solution to solve the Clutch overload loss
+ What is the solution to solve the Hydraulic pressure NOK loss
+ What is the solution to solve the Step control loss
- Action plant for the above solution?
+ In your opinion, what is the cause of the Breakout
The causes of damage in various forms can be attributed to specific factors For instance, the damage punch may result from excessive force or improper alignment during the punching process Similarly, damage from cutting the plate often stems from dull blades or incorrect cutting techniques Lastly, the belly notch can be caused by material fatigue or stress concentrations that lead to structural weaknesses Understanding these causes is essential for preventing future damage and ensuring the integrity of materials.
+ In your opinion, what is the cause of the Stuck conveyor
Solution discussion and action plan of A
+ What is the solution to solve the Breakout
+ What is the solution to solve the Damage punch + What is the solution to solve the Damage cutting plate + What is the solution to solve the Belly notch
+ What is the solution to solve the Stuck conveyor
- Action plant for the above solution?
The ejecting force generation system
Oring of the hydraulic pipe and joints
The gap between the conveyor and the partition wall