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A SMART KANBAN SYSTEM FRAMEWORK FOR MALAYSIAN AUTOMOTIVE MIX

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nida yasin

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Transcript of A SMART KANBAN SYSTEM FRAMEWORK FOR MALAYSIAN AUTOMOTIVE MIX

Problem Statement
Research Questions
Scope & Limitation
Literature Review
Research Methodology
Research Objectives
Project Background
Gantt Chart
By: Nur Nida Azira Binti Md Yasin
A SMART KANBAN SYSTEM FRAMEWORK FOR MALAYSIAN AUTOMOTIVE MIXED MODEL ASSEMBLY LINES

Conceptual Framework
Significance of the study
The complexity of manual kanban system has increased with the increase of product variety in mixed model production area and thus causes problems
(i) Inefficient kanban system due to wrong application of kanban type.
(ii) Production delay and wrong order due to incorrect number of kanban card in the system.
(iii) Insufficient inventory.
(iv) Late kanban card information to production area.
v. Ability to transfer production orders information from downstream to upstream by the material handler on time is always disputed.
To investigate the parameters limiting the conventional kanban system in an automotive subject company.
To demonstrate the framework using Quest software to support the assembly line performance.
To design the smart kanban system framework for mixed model assembly lines to solve the dynamic and complex problem of production planning.
Why manual kanban system ends-up with production problems such as production delays, insufficient inventory and late information to production lines in a mixed model production system?
How are the number of kanban and lot sizes of part types determined under a mixed model production environment?
How is the kanban system adjusted when misbehaved situation occur such as machine breakdown and lack of material supply?
How can an accurate and effective kanban system be developed in order to optimize the performance of a conventional kanban system?
Collect data at the automotive manufacturing industry.
The results are also not applicable for overseas automotive manufacturing companies since the observations are conducted based on Malaysian’s manufacturing environment.
The outcome of the results may not be applicable for other types of industry.
Focus on automotive industry since most automotive vendor are interested to apply and adopt kanban to realize a world class manufacturing level.
New technology on the smart kanban system framework development for mixed model production area for automotive manufacturers in Malaysia. The production planning can be setup easily by the worker.
Improve the productivity performance, lead time and inventory level for manufacturing companies.
Kanban System
Mixed Model Production Line
Electronic Kanban System
Development Simulator for Operation of Kanban System.
Objective:
To develop kanban simulator to support information for design of operation.
The effect optimum number of Kanban in Just In Time production system to manufacturing performance.
Objectives:

1)To determine number of kanban in JIT production system.
2) To analyzes effect of optimum numbers of kanban to manufacturing performance.
Study on Carrying out Kanban Production System in a Engine Assembly Workshop.
Objectives:
1) To analyzed the production status of an engine assembly plant.
2) To identified the problem reduced production efficiency.
3) To proposed re-introduction of kanban production system to help enterprises overcome the present impasse.

Levelling-based Kanban calculation in production system
Objectives:
1) To define replenisment time based on leveled production and proposes an improved method of kanban calculation.
2) Method of kanban calculation could be improved and completed, it considers 4 factors; replenishment time, lot size, customer withdrawal, safety stock.
Electronic Kanban System
Objective
: To study the role of E-kanban in JIT production system at Oral-B tooth brush company.
An E-kanban System for Fork Truck Assembly Lines
Study on Electric Kanban Management System in Steel Structure Engineering of an International Expo Centre
Objectives:
1) To eliminate the current problem in construction industry
2) To determine what to produce, when to produce and how to produce.
3) To help pull production, enhance production efficiency, reduce waste, shorten schedule.
4) To solve problem of schedule delayed, cost out of control and low production efficiency and to promote the development of construction industry.
The Electronic Kanban System for Mixed Model Assembly Based on Simulated Annealing Algorithm
Objectives:
1) To determine the number of kanban and lot sizes of part types.
2) To maximize the percentage zero demand.
3) To reduce the mean lead time.
4) To reduce cost of transports.
Scheduling Utility Workers at Mixed-Model Assembly Lines
Objective:
To investigate a potential of cutting labor costs at mixed model assembly line where utility workers are deployed.
Balance Problem Research of the Mixed Model Assmbly Line
Objective: To s
tudy the problem of balancing the load of work stations and the parts consumption rate by adjusting manufacture sequence that the work station and tact have ben optimal determined.

Project Flowchart
Phase 2
Phase 3
Phase 5
Phase 4
Phase 1
Phase I: Preliminary study
Phase II: Data collection at UASB
Phase III: Design of Smart Kanban System Framework
A new Smart Kanban System Framework will be designed based on the real condition of the UASB. Specific kanban formulation and calculation as practiced and developed by Toyota will be used in order to design a smart and practical framework to be used by all level of workers. Computer programming will be applied to develop numerical calculation method for selecting the kanban type and determination of the kanban card quantity.
Phase IV: Demonstrate the framework using Delmia Quest
The output from framework then used to create an assembly model using Quest software. The model aims to demonstrate and support the performance of new smart kanban framework. Therefore, reliable results and feedbacks from the Quest simulation can be analyze to optimize the effectiveness and practicability of these systems.
Phase V: Results evaluation, discussion, conclusion and final report writing
The data generated from Quest simulation the will be compared to the current assembly line performance, then the result evaluated, discussed and concluded to produce final results that will be included in the final report.
M.Raju Naik(MS), E.Vijaya Kumar(M.Tech), B.Upender Goud (BA)
Findings
:
1) Conventional kanban should be substitute with E-kanban system.
2) E-kanban works more effectively and efficiently with lean process.
3) The transparency of supply chain is very much increased with the implementation of E-kanban system.
4) Very important to take into consideration of the financial things of the system. Its involves high investment.
5) Very big successful if the implementation of the system is well-done as if helps in optimization of the process.
On Solving JIT Production Problems for Small Batch Orders Based on E-Kanban Visualisation
Jin Qing, Pan Xue-tao, Zhang Zhong
Objectives
: To solve the bottleneck problem of the traditional JIT production mode in the mixed model production of the small batch production based on an improved kanban technique.
Findings:
1) Integrate with the information system has the simulation and the prediction function and promotes the plan ability.
2) Transparence and intuition of the kanban procedure and situation.
3) Can display overall and real time various working procedure and the actual situation in the E-kanban.
Rong Hu, Fei Gao and Cheng Gong
Guo Jun Li, Teng J Ying, Li Shu Qin
Findings:
1) Kanban management is beneficial to intergrated construction information establish and to better information sharing.
2) Increase the accuracy and the speed of information flow and material flow
Objectives:
1) To control inventory levels, production and supply of components and in some cases, raw materials.
2) To be more responsive with lower inventory costs.
Findings:
1) Kanban theory is good to solve the problem about overstock of in-process material in current fork truck plants.
2) Traditional kanban has many limitation such as wasting paper, adding cost, non-flexible management, low efficiency, and so on.
3) E-kanban can auto-updatethe kanban information.
4) After practice e-kanban, the space of assembly line is saved 25%, stock in process material in the fork truck plant is reduced 40%
5) Much more potential quality problems are solved 6) cost is economized
Wang Haiyan
Findings:
1) The traditional kanban cant help in the complex situation to deal
with so much information to adjust itselft dunamically and quickly.
2) Can easily solve problem.

Ahmad Naufal Adnan, Ahmed Jaffar, Noriah Yusoff and Nurul Hayati Abdul Halim
Findings:
1) Product lead time reduced by 36%.
2) Inventory on floor improved and reduced by 81%.
Yan Xiao, Yunyun Li, Qiuhong Jia.
Findings:
1) Workshop environment is improved and the corporated image is enhanced.
2) Long term friendly cooperative relations with supplier are established.
3) Product quality is greatly improved, customer satisfaction increased.
4) Team spirit is strengthened and enterprise is more cohesive.
5)production information is delivered directly to the final process so it is more timely and accurate.
Qianwang Deng and Jieyou Wang.
Findings:
1) Combining leveled production into consumption controlled loop could define repenishment time more specific and accurate. 2) Kanban calculation have to consider 4 factor; replenishment time, lot size, customer withdrawal, safety stock .
3) Replenishment time and kanban number are very important to help manufacturer to order raw material, adjust production plan and meet the customer requirement.
Parameter Optimization of Kanban Production System for an Engine Assembly Workshop Based on Witness
Yan Xiao, Yunyun Li, and Kangqu Zhou.
Objectives:
1) To raise utilization rate of machine and production output, reduce WIP inventory, waiting time for order.
2) To maximum production efficiency of equipment the minimum work in inventory, the minimum the average waiting time for order and the largest volume of production.
Findings:
1) Increased capacity utilization, total output.
2) Reduce average delay time of the order.
Beom Seok Oh and Jae II Park.
Findings:
1) Operation of establish kanban is possible to control visually.
2) The limit is hard to control well totall.
Feng Jun Xia, Wang Zhan-Zhong, Jin Feng Hua and Yu Liu Qing.
Finding:
Differences in product types and technology lead to increasing the complexity of assembly balancing.

Rico Gujjula, and Hans-Otto Gunther
Findings:

1) Utility work is a very important performance parameter for sequencing mixed model assembly line.
2) There is a potential of cutting labor costs by using the anticipative approach for scheduling utility workers.

A New Procedure of Production Orders Sequencing in Mixed-Model Production System
Zemzack Marcin, and Krenczyk Damian
Objectives:
1) To establish a proper sequence of tasks.
2) To maximize the utilization of company's production capacity.
3) To determine the effective method of creation of task sequence.

Findings:
1) The experiment have shown the correctness and usefulness of the proposed sequencing system.
2) Approprite sequencing of production orders in the case of mass linear mixed model production systems is a key factor, since it has a significant impact on efficiency throughout the whole enterprise.

Sequencing mixed-model assembly line under a JIT-approach
Neda Beitollahi Tavakoli and Parviz fattahi.
Objectives:
1) To study the sequencing mixed model assembly line problem with a JIT supply of required of material.
2) To avoid/ minimize sequence-dependent work overload bsed on operation time, worker movement, station border.

FIndings:
Improve total utility time, total idle time, lunch interval, total cost criteria and the total deviation criteria.

Production Orders Sequencing in Mixed Model Assembly Lines
Zemzack marcin
Objective:
To determine the effective method of creation of task sequence
Finding:
Appropriate sequencing of production orders in the case mixed model production impact to efficiency.
Mixed-model Flow Production Scheduling Method Based on Multi-Agent and Hybrid Genetic Algorithm
Linghong Lai
Objective:
To investigate optimal production scheduling method to solve complex production scheduling problem.
Finding:
Hybrid genetic algoritm can provide can approach to
adapt to complex and dynamic production scheduling.


The complexity of manual kanban system has increased with the increase
product variety.
Ends-up with manufacturing problems; 1)production delay due to wrong order and incorrect number of kanban cards in the system, 2)insufficient inventory, 3)late information to production area.
Imperfect situation;
1)surging order,
2)machine breakdown,
3)high fluctuation of demand,
4)operation failure.
Shortage of the delivery will then occur and the only solution is to have a huge amount of safety stock.
Increase inventory cost.
High demand fluctuation.
Lost of kanban card often occurs.
Paper kanban card and its data complicated to transmit directly to computer.
Electronic kanban introduced to replace the manual kanban in order to solve the current problems.
No change in the current practice.
But boosted and improved the kanban application in production line.
Transparency of the real kanban procedure and situation.
Display overall and real-time various working procedures and the actual situations in the computer screen.
When abnormal situation occur, the electronic kanban system can adjust production scheduling.
Suggest other valid kanban data for all kind of situation.
Supervisor Name: Assoc. Prof. Roseleena Binti Jaafar
Co-Supervisor Name: Nurul Hayati Binti Abdul Halim
Student ID: 2014258266
The result validate through the simulation software.
Develop the electronic kanban system through numerical method.
Scopes
Limitations
Identify the research gap.
Searching for potential research methods and understanding.
Understanding characteristics of mixed model manufacturing areas.
Determine factor limiting in mixed model manufacturing areas.
Understanding the conventional kanban system.
The previous six month manufacturing parameters such as line cycle time, demand history, production output, productivity, lead time
The approach of working place observation will be used to gather all the parameters. Proven TPS tools like standardized work spreadsheet and time study will be used
Informal interview will be conducted to three different levels of workers which are the production engineer, line leader and operator. The questions are designed to suite the different level of workers with the corresponding objective from each worker.
Production engineer are focuses on gather information about the production planning procedure, kanban card formulation, production performance trend. However for line leader and operator more focus to look into the real production situation, worker satisfaction,worker adaptation, task obstacle, frequent card losses, material handling system and so on.
List of References
1. Cao Zhenxin, “ Optimal Research on Balancing and Sequencing of Mixed Model Assembly Lines”, Information and Control, Vol. 33 (2004), pp 660-664.
2. Jin Qing, Pan Xue Tao and Zhang Zhong, “ On Solving JIT Production Problems for Small Batch Orders Based on E-Kanban Visualization”, 3rd International Conference on Measuring Technology and Mechatronics Automation, IEEE (2011), pp 757-761.
3. Guo Jun-li, Teng Jia-ying, Li Shu-qin, Wan Dong-yan and Jiang Xue, “ Study on Electronic Kanban Management System in Steel Structure Engineering of an International Expo Centre”, Advanced Materials Research Vol. 621 (2013), pp 375-380.
4. Zhang Jun,” A Study of Assembly Production Monitoring System Based on RFID and Electronic Kanban”, Zhejiang University, (2007).
5. Wang Haiyan, “The Electronic Kanban System for Mixed Model Assembly Based on Simulated Annealing Algorithm” , Advanced material Research, Vols. 403-408 (2012) pp 4355-4359.
6. V. Tardif and L. Maaseidvaag, “ An adaptive approach to controlling kanban systems” ,European Journal of Operational Research, (2001), 132(2), pp 411-424.
7. C.S Kumar and R. Panneerselvam, "Literature review of JIT-KANBAN system," International Journal of Advanced Manufacturing Technology, 32(3-4): 393-408.
8. N. Singh, K. Shek and D. Meloche, “The Development of a Kanban System: A Case Study,” International Journal of Operations & Production Management, 10(7), pp 28-36.
9. J. Matzka, M. Di Mascolo and K. Furmans, “Buffer sizing of a Heijunka Kanban system,” Journal of Intelligent Manufacturing, 23(1), pp 49-60.
10. F. Chan, “Effect kanban size to JIT manufacturing system,” Journal of Materials Processing Technology, (116), pp 146-160.
11. S. Jarupathirun, A. P. Ciganek, T. Chotiwankaemanee and C. Kerdpitak, “Supply Chain Efficiencies through E-Kanban – A case study”, Int. Conference, (2009).
12. Ahmad Naufal Adnan, Ahmed Jaffar, Noriah Yusoff and Nurul Hayati Abdul Halim, “ The Effect of optimum number of Kanban in Just In Time production system to manufacturing performance”, Applied Mechanics and Materials, Vol. 315 (2013), pp 645-649.
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14. Yan Xiou, Yunyun li and Qiuhong Jia, “ Study on Carry out kanban Production System in a Engine Assembly Workshop”, Advanced Material Research, Vols 424-425 (2013), pp 330-333.
15. Yan Xiao, Yunyun Li, and Kangqu Zhou, “Parameter Optimization of Kanban Production System for an Engine Assembly Workshop Based on Witness”, Advanced Material Research, Vol. 382 (2012) pp 252-255.
16. Zemczak Marcin, “ Production Orders Sequencing In Mixed Model Assembly Lines”, Applied mechanics and Materials, Vol. 657 (2014) pp 359-363.
17. Feng Jun- Xia, Wang Zhan Zhong, Jin Fen Hua and Yu Liu Qing, “ Balance Problem Research of the Mixed Model Assembly Line”, IEEE, (2010), pp 264-266.
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19. Zemczak marcin, and Krenczyk Damian, “A New Procedure of Production Order Sequencing in Mixed Model Production Systems’, Advanced Material Research Vol. 1036(2014) pp 864-868.\
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21. Rico Gujjula and Hans-Otto Gunther, “ Scheduling Utility Worker at Mixed model Assembly Lines”, IEEE, (2009), pp 1092- 1096.
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Inventory problem
Papery kanban card.
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