CONTROL OF WIP AND REDUCTION OF LEAD TIME IN A FOOD
PACKAGING COMPANY
by
MASAUET~TS INTITTOF TECHNOLOGY KEVAN YONG CAI CHIM
NOV 0 42010
B.Eng., Mechanical Engineering (2009)
LI
BRARI ES
Nanyang Technological University, Singapore
SUBMITTED TO THE DEPARTMENT OF MECHANICAL ENGINEERING IN PARTIAL
FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF
ARCHIVES
MASTER OF ENGINEERING IN MANUFACTURING AT THE
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
SEPTEMBER 2010
C20 10 Massachusetts Institute of Technology. All rights reserved.
( /
Department of Mechanical Engineering August 18, 2010
Certified by:
Accepted Dy:
Stephen C. Graves Abraham J. Siegel Professor of Management Science Department of Mechanical Enginng and Engineering Systems TJhesi Sunervisor
David E. Hardt Ralph E. and Eloise F. Cross Professor of Mechanical Engineering Chairman, Committee on Graduate Students
CONTROL OF WIP AND REDUCTION OF LEAD TIME IN A FOOD
PACKAGING COMPANY
by
KEVAN YONG CAI CHIM
Submitted to the Department of Mechanical Engineering on August 18, 2010 in partial fulfilment of the requirements for Degree of Master of Engineering in
Manufacturing
Abstract
High inventory holding costs, strain on warehouse capacity and the competition of lead time are concerns of a food packaging manufacturer. In this work, causes of high WIP were identified and three approaches were developed to reduce and control better the WIP. We propose to split the production line into dedicated lines, to change the push production system to a pull production system, and to align the process times to the takt time. A simulation model of the proposed production line was analyzed and was verified
by a simulation model of the current production line. Three configurations were tested for
production line A and production line B. We found that the proposed production line reduced the WIP by 70% and saved $990,000 annually in inventory holding costs. In addition, the lead time was reduced from 6.4 days to 1.9 days and the strain on the warehouse capacity was eliminated.
Thesis Supervisor: Stephen C. Graves
Table of Contents
C hapter 1: Introduction ... ...--- 1
1.1 Com pany background ... 1
1.2 Com pany products ... 1
1.3 M arkets and custom ers ... 3
1.4 CA S operations ... 5
1.4.1 D esign departm ent ... 6
1.4.2 Planning departm ent ... 6
1.4.2.1 M aterials planning ... 6
1.4.2.2 Production planning ... 7
1.4.3 Production departm ent ... 8
1.4.3.1 Pre-press process... 9
1.4.3.2 Printing process... 10
1.4.3.3 Lam inating process ... 11
1.4.3.4 Slitting process... 12
1.4.3.5 D octoring process ... 13
1.4.3.6 Palletizing process ... 13
1.4.4 Storage and w arehousing ... 13
1.4.5 Purchasing departm ent... 15
Chapter 2: Problem statement...16
2.1 Project m otivation... 16
2.1.1 H igh inventory holding cost... ... ... 16
2.1.2 Exceed w arehouse capacity ... 17
2.1.3 Com petition of lead tim e ... 18
2.2 Causes of high W IP ... 20
2.2.1 Com plexity... 20
2.2.2 Local autonom y of production rate... 20
2.2.1 Em phasis on O EE ... 21
2.2.1 Push production system ... 21
C hapter 3: Literature review ... 23
3.1 Little's law ... 23
3.2 Push and pull production system ... 24
3.2.1 M aterial and inform ation flow ... 24
3.2.2 Control of W IP and throughput ... 25
3.3 K anban system ... 25
3.4 Conw ip system ... 26
3.4.1 N um ber of cards... 27
3.4.2 Stress level of w orkers... 27
3.5 Sim ulation... 28
C hapter 4: M ethodology... 29
4.1 Problem solving phase ... 29
4.2 D esign proposed production line ... 30
4.2.1 Changes to current production line ... 30
4.2.1.1 Dedicated production lines ... 30
4.2.1.2 Pull production system ... 33
4.2.1.3 Takt tim e ... 34
4.2.2 Selection of dem and... 36
4.2.3 Products allocation... 38
4.2.4 Sequence of production... ... ... 42
4.2.5 W ork station stoppage... 44
4.3 Sim ulation m odeling... 48
4.3.1 Proposed production line ... 48
4.3.2 Current production line ... 51
4.4 Im provem ent analysis ... 53
4.4.1 Conversion betw een rolls and reels ... 53
4.4.2 Inventory holding costs... 54
C hapter 5: R esults and discussion... 55
5.1 Current production line ... 55
5.2 Line A perform ance ... 56
5.2.1 Throughput and card num ber... 56
5.2.2 W IP inventory ... 57
5.3 Line B perform ance ... ... 59
5.3.1 Throughput and card num ber... 59
5.3.2 W IP inventory... 60
5.4 Inventory level and holding costs ... 63
5.5 W arehouse capacity ... 65
5.6 Lead tim e ... 67
Chapter 6: R ecom m endations and conclusion... 68
C hapter 7: Future opportunities ... 70
Table of Figures
Figure 1.1: Major Products of CAS... I
Figure 1.2: The different layers of a package... 2
Figure 1.3: Markets served by Company A... 3
Figure 1.4: Order Flow Diagram... 5
Figure 1.5: Block planning system... 8
Figure 1.6: An overview of the manufacturing processes... 9
Figure 1.7: Cliche used for printing... 9
Figure 1.8: M ounted sleeves... 10
Figure 1.9: The Printing Process... 10
Figure 1.10: The Laminating Process... I1 Figure 1.11: Process of slitting station... 12
Figure 1.12: Capacity of warehouse... 14
Figure 2.1: Inventory holding costs for 2009... 16
Figure 2.2: Warehouse capacity for printed, laminated and doctor WIP... 17
Figure 2.3: Lead tim e... 18
Figure 2.4: Comparison of lead time with other factories... 19
Figure 2.5: Mixed flow production... 20
Figure 3.1: Queuing system... 23
Figure 3.2: Material and information flow in a push system and pull system... 25
Figure 3.3: Kanban system... 26
Figure 3.4: CONWIP system... 26
Figure 3.5: Steps in a simulation study... 28
Figure 4.1: Phases of problem solving... 29
Figure 4.2: Dedicated production lines... 32
Figure 4.3: Pull production system with card return... 34
Figure 4.4: Simulation model of proposed production line... 48
Figure 4.5: Simulation model of current production line... 51
Figure 4.6: Slitting of a roll into reels... 53
Figure 5.1: Throughput trend of line A... 56
Printed WIP with L22 process time = 14minutes ...
Printed WIP with L22 process time = 12minutes ...
Inventory cost of proposed production line... ... Capacity of printed and laminated WIP... ...
Capacity of doctor WIP... Lead time of proposed production line... ... Figure 5.3: Figure 5.4: Figure 5.5: Figure 5.6: Figure 5.7: Figure 5.8:
List of Tables
Table 1.1: Shipping schedules... 4
Table 4.1: Work station capabilities... 30
Table 4.2: Takt time of work stations ... 36
Table 4.3: Demand of first three months in 2010... 36
Table 4.4: Demand breakdown of March 2010... 37
Table 4.5: Maximum rate of work stations... 38
Table 4.6: Products allocation based on initial assignment ... 39
Table 4.7: Products allocation after demand adjustments ... 41
Table 4.8: Setup costs of laminators ... 42
Table 4.9: Sequence of production ... 43
Table 4.10: Breakdown of work stations ... 44
Table 4.11: Rest time of work stations ... 45
Table 4.12: Short stop of work stations ... 45
Table 4.13: Setup time of work stations... 46
Table 4.14: Reel inspection time of slitters ... 47
Table 4.15: Process time of work stations in proposed model ... 50
Table 4.16: Percentage of rolls processed by each work station ... 52
Table 4.17: Process time used in current production line model ... ... 52
Table 4.18: Inventory holding costs of three types of WIP ... 54
Table 5.1: Performance of the current production line model ... ... 55
Table 5.2: Error in the current production line model ... 55
Table 5.3: Throughput mean and standard deviation in line A ... 57
Table 5.4: Average printed WIP in line A ... 58
Table 5.5: Average laminated WIP in line A ... 58
Table 5.6: Average doctor WIP in line A ... 58
Table 5.7: Throughput mean and standard deviation in line B ... 60
Table 5.8: Average printed WIP in line B ... 60
Table 5.9: Average laminated WIP in line B ... 60
Table 5.10: Average doctor WIP in line B ... 61
CHAPTER 1: INTRODUCTION
1.1 Company Background
Company A, Singapore (CAS) is a multinational food processing and packaging company of Swedish origin. Founded in 1951, it is one of the largest manufacturers in the food processing and packaging industry. Company A provides integrated processing, packaging and distribution lines as well as plant solutions for liquid food manufacturing. Today, the business spans more than 150 countries with 43 packaging material production plants worldwide.
CAS was established in 1982. CAS focused on manufacturing finished packaging
material for customers in 19 countries. CAS and Company A, Pune, in India are the production plants in the South and Southeast Asia Cluster. In year 2007, CAS received the Manufacturing Excellence Award (MAXA) for overall excellence in innovations, operations and sustainability as well as its World Class Manufacturing (WCM) approach to ensure operational improvement and downtime minimization.
Due to the increase in complexity of Company A's supply material plants worldwide and increase in both complexity and number of products, Company A has been focusing on improving their supply chain and production efficiency.
1.2 Company Products
Company A is one of the world's major packaging providers. It offers a wide range of packaging products, filling machines, processing equipment, distribution equipment and
services. Figure 1.1 shows the major products of Company A.
CAS produces carton packs, also known as CA packs. CA packs are used for food items
like milk, juice and soy products. Designing service is also available for customers. Each
CA pack is made of 6 layers of materials, including aluminum, paper and polyethylene,
to prevent spoilage of the content. The base material for each package is paper. It provides structure and support to each package. After the design is printed onto the paper, it will be coated with a layer of aluminum foil, which makes the pack aseptic and preserve the flavor of the content. Four layers of polyethylene will also be coated onto the paper. The outside layer prevents damage from moisture; the adhesive layer between the paper and aluminum foil provide structure support and two protective innermost layers seals the liquid content. The layers of the package and their respective functions are shown in Figure 1.2.
1.PE -protects against outside 5
moisture & enhance appearance & 2 Paper -for stability and 2
strength
3.PE -adhesion layer 4. Aluminium foil -oxygen, flavour and light barrier 5.PE -adhesion layer 6. PE -seals the liquid
Figure 1.2: The different layers of a package.
There are 10 classes of package available for CA packs. They are Brik, Brik Aseptic, Prisma Aseptic, Gemina Aseptic, Fino Aseptic, Classic Aseptic, Wedge Aseptic, Rex, Top and Recart. Different sizes are offered for each class of package, while the polyethylene layers are different for different carton content.
Currently, different products are distinguished by the system code, size code, quality code and design code. The system code defines the class of the package, which describes whether the carton is aseptic, refrigerated or ambient. Different classes require different creasing in the printing stage. System codes also have a suffix indicating the content of
the carton (juice or milk), which would affect the laminating stage as different contents require different polyethylene formulations. The size codes indicate the volume of liquid contained by the package and its shape (slim, base, square). Thus it describes two attributes and affects the printing, slitting process and sorting on the laminator. Products with the same size code would have same overall width and therefore, same number of webs. Quality codes determine the type, thickness in grams per square meter and the brand of paper used. Lastly, design codes describe a single attribute that is the design of the product.
Compared with other factories of company A, CAS offers a large range of different CA pack products. Currently, around 20 different products of different package classes, carton sizes and polyethylene formulations are able to be produced in CAS.
1.3 Markets and Customers
Positioned in Singapore, CAS efficiently serves customers in the South and South East Asia cluster. There are also customers from Europe and the Middle East. In total, CAS ships its finished products to customers in 19 different countries, as shown in Figure 1.3.
The customers of CAS currently need to place their orders through a market company. The market company has a sales office in the customers' respective country. They take orders from beverage producing companies then receive and distribute the finished products to the customers.
The Thailand market is the largest by volume, followed by Malaysia, Indonesia and Vietnam. Most of the products are ocean freight to the customers. At the moment, only the Malaysia market is being served by truck freight. For most shipping routes, the containers are only picked up from Singapore ports twice a week and the shipping dates are fixed. For example, for the case of the Thailand market, finish goods are shipped out on every Tuesday and Saturday. For the Malaysia market, the freight truck delivers orders from CAS everyday. The details are documented in Table 1.1 below.
Table 1.1: Shipping schedules.
usrana nu, bun Zealand ue, Thu
hina on, Thu akistan Mon
ng Kong us, Sat Hiippines ue, Sat ndonesia hu, Sun audi Arabia ue
pan tanka ri
Korean Mon, Fri aiwan Mon, Wed
laysia Daily land ue, Sat
epal on let Nam Mon, Wed, Thu
1.4 CAS operations
The core corporate functions of CAS are the design, production, planning and purchasing departments. There is also a market company operating in CAS' premises and this is an independent entity from CAS. The market company is responsible for order management and customer service. CAS' warehouse and delivery operations are outsourced to a third party logistic company. Figure 1.4 shows the steps at which an order is processed.
*Goods are being delivered out of the warehouse everyday
1.4.1 Design Department
After the customers' designs have been submitted to CAS's design department, the design department reviews and adapts these designs to suit CAS's production systems. When faced with difficulty, the customers do receive assistance from the design department in designing the carton. Once the design is confirmed, the design is broken down according to the component colors. The process colors are Cyan (C), magenta (M), yellow (Y) and black or key (K). Special or spot colors may also be used to obtain specific shades of color. The number of spot colors can vary from none to seven. A sales order can only be made once the designed is confirmed.
1.4.2 Planning Department
The planning department at CAS is responsible for materials planning and production planning.
1.4.2.1 Materials Planning
Materials Requirement Planning does the ordering of the raw materials needed for production. The base materials ordered are paper, polyethylene and aluminium foil with many types of variants in terms of grade and size. The purchasing department is responsible for acquiring the additional materials such as water based inks, pallets and tapes that are used for production as they are relatively low volume and low cost.
Company A International (CAI) is the parent body of CAS. CAI issues the annual global forecasts for number of packs and marketing directives. CAI's Global Supply places blanket orders on the basis of the annual forecast for each of the converting factories with the suppliers in order to obtain economies of scale and to pool the variation in demand. The converting factories then place the actual orders with the suppliers to withdraw from the blanket order placed initially.
In addition, monthly forecasts are also issued and updated regularly. As the lead time of raw materials is very long, the ordering is done well in advance. The ordering is done on a weekly basis as this time period coincides with the frequency of dispatch. A continuous
review method is used to determine the ordering quantities. The re-order point is set at approximately 40% of the monthly demand while the order up-to point is around 60% of the monthly demand.
1.4.2.2 Production Planning
The production system of CAS is make-to-order. The production schedule is drafted only upon receipt of a production order from the sales department. The scheduling is done on the SAP based P2 system and the current production lead time is around 12 days. Planning is based on the delivery due date. CAS uses three core work stations for their processes. They are the printer, laminator, and slitter. On each of the three work stations, the orders are grouped together based on certain criterions to minimize setups. The grouping for the printer is done on the basis of size and shape. The criterion for the laminator is the overall width of the roll. Lastly, the slitter orders are arranged based on pack width.
A block scheduling system is used to plan the production schedule. In this collaborative
planning, the planning department generates a weekly production schedule with blocks according to width of the paper rolls. This is to reduce the number of setups at the laminator. Customer orders are then fitted into the blocks. The latest order date for the customers is 4 days before the production cycle starts. The production cycle starts on every Monday. Thus, the customers must place their orders by Thursday of the previous week. The estimated delivery date is 3 days after the end of the production cycle. Therefore, the products would be ready on the Wednesday after the production cycle. The customers would be able to place orders many weeks earlier. However, when the orders are placed too early, the orders would be kept in the system and be produced in the subsequent production cycles. Figure 1.5 shows the block planning.
However, some customers tend to place last minute orders, which would create disruptions to the planned production schedule. These last minute orders are rush orders which lower equipment efficiency. These last-minute orders are urgent orders that are placed within 1 to 3 days before the start of the production cycle in which it needs to be produced in. Also, when the current production schedule has been completed ahead of
time, the planning department would also bring forward some orders to fill up the empty block in the block schedule. By doing this, the equipment efficiency is improved but advanced production will also result in higher work in process (WIP) and finished goods inventory.
4 days
7 days
3 days
M T
W TH F
S S
Latest order
Production cycle
Estimated
date
delivery date
Figure 1.5: Block planning system.
1.4.3 Production Department
The Production Department performs the major manufacturing processes to produce the packing materials. The 3 major processes in CAS are printing, laminating and slitting. Before printing, a pre-press process has to be carried out, and after slitting, a doctoring process sometimes needs to be done. An overview of all the production processes is shown in figure 1.6.
PRODUCTION PROCESS
SR~MDPAM WAM BASMDI PBOD
L~IHNENG
PALLETZEG PA
Figure 1.6: An overview of the manufacturing processes.
1.4.3.1 Pre-Press Process
This is the first stage in the production process. In the pre-press stage, the clich6s for printing are prepared from the negatives. The cliches are polymeric stamps with elevated portions for the areas to be printed. These clich6s are prepared on photopolymer plates through a process of controlled exposure to UV light. There will be a cliche prepared for each color used for printing. After which, the cliches are mounted onto a sleeve with a rotating spindle. The number of cliches mounted on one sleeve depends on the width of the individual pack and the paper roll. This corresponds to the number of webs. A cliche used for printing is shown in figure 1.7. Figure 1.8 shows the mounted sleeves.
Figure 1.7: Cliche used for printing.
Figure 1.8: Mounted sleeves.
1.4.3.2 Printing Process
In the printing stage, the flexography method is used. This is a method of direct rotary printing that uses resilient relief image plates of photopolymer material. The design pattern on the cliches is reproduced onto the paper board by rotary contact of the paper roll with the stamp. Water based ink is used. The incoming paper roll is loaded on the un-winder, which opens it up and feeds it to the printing stations. An illustration is shown in
Figure 1.9. Ink transferred Impression Cylinder Ink transferred from anilox to plate Doctor Chamber
There are seven stations on the printer. Each station holds the sleeves and the water based inks for one of the colors of the design. Depending on the design colors, some of the stations may be idle for a design as not all colors are used for every design. A colored image is formed by 4 process colors, Cyan (C), magenta (M), yellow (Y) and black or key (K). The different colors are then superimposed one over the other to get the
complete final printed design.
Fold creases for the produced cartons are also form during the printing process. The purpose of creasing is to enable proper folding of the pack during the filling stage at the customer site. The tool is used to form creases also punched the holes for straws. For routine printing, flexographic technology is used. For higher resolution designs, CAS uses offset printing, which is more expensive compared to flexography.
1.4.3.3 Laminating Process
Laminating involves the coating of aluminum foil and polyethylene (PE) layers onto the printed paper. A roll is first unwound at the unwinder. It then goes through three stations for the coating process. The last step is to rewind the laminated paper into a roll. In the first station, a layer of aluminium foil is layered onto the printed paper. After which, PE film is coated in the inner surface of the packaging material to prevent contamination and leakage. The final station adds another layer of PE on the outer surface of the packaging material to protect the paper. This process is shown in figure 1.10.
Polymer
Laminator I Lwminhtor2 Laminator3 Laminate layer inside layer D6cor layer
Figure 1.10: The Laminating Process.
1.4.3.4 Slitting Process
The paper roll can have 4, 5, 6, 7, 8 or 9 webs (columns) depending on the product size.
The slitting process cuts the entire roll into reels of a single pack width so that they can be fed into the filling machines at customer production plant. The rolls are unwound, slit using a row of knives and counter-knives and then rewound to form reels. The reels are then grouped into defective reels and non-defective reels. Defective reels are reels that consist of at least one defect and these reels need to go through the doctoring process to have the defects removed. Non-defective reels are reels which have no recorded defects throughout all the processes and they do not need to go through the doctoring process. A schematic diagram of slitting process is shown in figure 1.11.
1.4.3.5 Doctoring Process
After the slitting process, the defective and defective reels are separated. The non-defective reels would be kept at the shop floor and the non-defective reels would be doctored. Doctoring or rework is the process of removing the packs with defects from the reels. Approximately 24% of the reels require doctoring. These defects are due to any of the upstream processes and they are removed collectively at this stage. There are 14 doctoring stations after the slitting process. Each doctoring work station would have an operator to find the defects and remove them using a machine. One reel could be doctored every 24 minutes on average by an operator.
1.4.3.6 Palletizing Process
The doctored reels would join the good reels to be palletized. Palletizing is the process of stacking reels together on a pallet and wrapped with a plastic layer. There would be 5 reels on the pallet on average. The palletizing time is 8 minutes. The palletized reels would be transported to the warehouse and await delivery. These palletized reels are handled solely by a third party logistics company from this point onwards.
1.4.4 Storage and Warehousing
CAS' in-house warehouse is shared among raw materials; work in process (WIP) and part
of total finish good inventory (FGI). Currently, the in-house warehouse is managed by a third-party logistics company.
The current daily FGI level is around 1000 rolls (converted from pallets), among which up to 600 rolls are stored in the internal warehouse. Each roll is approximately 5513m long and it takes up about 3 pallets. The current daily FGI level of about 1000 rolls is approximately equal to about 6 to 7 days of inventory as CAS produces approximately
130 to 150 rolls per day on average. The external warehouse is engaged when there is not
enough space. The floor layout and capacity for each category of inventories are illustrated in figure 1.12. As we can see from the figure, the full capacity for WIP is approximately 500 rolls only. Yet currently, average WIP levels can reach over 1000
rolls, not including raw material rolls. The raw material rolls are stored in a huge container yard beside the warehouse and it can hold up to 800 rolls of raw material. The movement of raw material, WIP and FGI between the production floor and in-house warehouse is facilitated by the laser guided vehicles (LGVs). These vehicles can move a roll at a time and they are programmed to follow a specific route. Forklifts and clamp trucks are used for the movements of the rolls within the internal warehouse.
1800
100
70
FG Storage Area (Pallets)
Alum Foil Storage Area (Crates/Boxes)
Additional Storage Area (Pallets)
Paper Storage Area (Rolls)
WIP Storage Area (Rolls)
Doctor Reels Storage Area (Pallets)
200 Malaysian Picking and Storage Area (Pallets)
Total Warehouse Storage Space
Figure 1.12: Capacity of warehouse.
Capacity
700
500
100
---1.4.5 Purchasing Department
The purchasing department at CAS is responsible for the purchase of additional materials and indirect services. Examples of additional materials include inks, pallets, cores, straws etc. Indirect services mainly refer to equipment maintenance, electricity, and water utilities. The base materials comprise 60% of the total monetary value spent by the purchasing department, while additional materials and indirect services make up the remaining 40%. There are more than 10 suppliers for the additional materials and more than 500 providers for indirect services. The purchasing reviews all the suppliers regularly and will provide assistance when the suppliers are underperforming. The purchasing department has a well-established system to source for alternative suppliers. Hence, suppliers who consistently underperform will be substituted.
CHAPTER 2: PROBLEM STATEMENT
2.1 Project motivation
2.1.1 High inventory holding cost
CAS has incurred high inventory holding cost. The inventory holding costs of each
month in 2009 is shown in figure 2.1. The printed WIP holding costs is $315,305 for the year, while the laminated WIP holding costs is $570,372 for the year. The total WIP inventory holding costs is $885,677 for the year of 2009. CAS has a production of over 1.2 billion packs per month since March 2010. CAS' marketing company has projected that sales will grow at 12 percent annually. Therefore, CAS needs to produce over 1.35 billion packs by March 2011. As such, the inventory holding costs would be even higher in 2011. CAS would be able to reduce the capital tied up by the inventories by reducing the WIP. 120,000 N Laminated 100,000 * Printed 80,000 -60,000 40,000 20,000 -0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
2009
Figure 2.1: Inventory holding costs for 2009.
-2.1.2 Exceed warehouse capacity
CAS stores its WIP in the internal warehouse. Capacity has been allocated to different
types of inventory. The capacity allocated for printed and laminated WIP is 500 rolls while the capacity allocated for the doctor WIP is 500 reels. Doctor WIP is the term CAS uses to refer to the WIP awaiting to be doctored. Figure 2.2 shows that the WIP has exceeded the capacity allocated for them. This has two impacts. Firstly, it forced CAS to store WIP at forklift lanes. As such, the forklift operators have a harder time to retrieve the rolls and it might cause safety issues. Secondly, CAS has to relocate some of the finished goods inventory to the external warehouse. The external warehouse incurs additional expenses for CAS.
Printed and Laminated WP Doctor WIP
1000 1800 900 __ -__ 1600 -1400 --1200 7'A 1000 600 , -0 50 600 400 400 200 300 0_FbJn Jl c o e Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oc Nov Dec
2009 2009
2.1.3 Competition of lead time
The lead time quoted to customers is 12 days from time of order placement until the order is shipped by CAS. (The lead time from point of shipment until the receipt by customer is outside of the control of CAS. The shipment is arranged between the customer and the logistics company.) The production lead time takes up about 10 of these 12 days. The remaining 2 days is due to the handling of the finished goods by the 3rd party logistics
company. This long lead time is mainly due to the long waiting time between processes. An illustration of the current lead time is shown below in figure 2.3.
1 day <0.5 day 4 days <0.5 day 3 days <1.5 days
Figure 2.3: Lead time.
There is both internal and external competition on the lead time. The internal competition comes from the comparison of CAS and other factories within the same company. Figure 2.4 shows the lead time quoted to customers by other factories. The factories in India and China are of concern to CAS as they are the neighbouring clusters. The lead time at India is only one day behind that of CAS. The lead time of 7 days in China is 60% of that in
CAS. Thus, there is a strong internal competition. The external competition comes from
company C. Company C is able to quote a lead time that is comparable to CAS. CAS has a strong desire to shorten its lead time to stay ahead in the competition.
17 16 15 14 13 12 12 9 9 Others Others Others Others Others India CAS Others Company C Others Others China China China Others 0 2 4 6 8 10 I I 8 10 12 14 16 18 20
Figure 2.4: Comparison of lead time with other factories.
Smaller number = shorter lead time 7
7 7
2.2 Causes of high WIP
2.2.1 Complexity
CAS is using a mixed flow production such that a product can flow to almost any station
downstream (subjected to work station capability). This mixed flow production is shown below in figure 2.5. There is no clear route for the production. It is too complex for CAS to set an appropriate route at which the products are produced at each stage. The mix of orders for each week is different, and CAS has a fast pace environment. As such, it is difficult for the planners to determine a good routing plan. This difficulty is coupled with rush orders (i.e. orders made by customer after the weekly production cycle has started). The planned production route would be disrupted by these rush orders.
S52 D1 to D14 P13 L21 S54 Pal Queue S53 P18 L22 FGI Pa2 S55
Figure 2.5: Mixed flow production.
2.2.2 Local autonomy of production rate
There is no fixed rule to control the production rate of the individual work stations. Each process manager would be given a production schedule and sequence. However, they have the autonomy to choose the work station speed at each stage. As such, every stage is producing at different rates. The general rule is that the individual process must not starve the downstream process. Thus, the process managers will produce a suitable level of safety stock based on their judgment to prevent the starvation of the downstream processes. As there is no 'pacer' in the production line, the WIP tends to build up. When sufficient WIP has built up, the work stations are rested.
2.2.3 Emphasis on OEE
The overall equipment effectiveness (OEE) is an important key performance index (KPI) for the production employees as their bonuses are tied to this KPI. As such, every process has an incentive to process the rolls that will bring the OEE to the target OEE. This builds up unnecessary WIP.
2.2.4 Push production system
CAS is currently using a pure push production system. The system ignores the real
production shop-floor situation. Thus, the upstream work station continues to produce even when the downstream work station is having a breakdown or a long setup change. This causes the WIP to build up. The laminator is currently the bottleneck of the entire system and it is estimated to have a capacity of 100 rolls per day. CAS would estimate the capacities of all work stations to plan the production for the push system. However, it is difficult to estimate the capacity as the actual capacity of the work stations would be altered by variations. Thus, if the actual capacity of the laminator drops and the actual capacity of the printer increase, there would be more WIP between these 2 stages.
2.3 Project Objective
The author aims to improve the production system in CAS by the following means:
1) Control the WIP to reduce capital tied up by inventories and to eliminate the
problem of warehouse capacity.
2) Reduce the lead time to keep CAS competitive in the industry.
3) Reduce the complexity of the production system to have better visibility and
CHAPTER 3: LITERATURE REVIEW
3.1 Little's law
Lead time and inventory level are two major concerns in a production system. A discrete-parts production system can be viewed as a queuing system where the items are queuing to be processed by a number of steps. Little's law offers an understanding on the queuing system. A simple queuing system is shown in figure 3.1. The work items arrive at the system where there is one server. The rest of the work items that are not served immediately have to wait in a queue for their turn to be processed. When a work item is processed by the server, it departs from the system. The Little's law relates the average number of items in a queuing system, the average arrival rate for the work items and the average queue time of work items by Eq. (3.1) [1]
L = XW Eq. (3.1)
Where L=average number of work items in queuing system A=average arrival rate of work items
W=average queue time of work items
Arrival
Departure
Queue
Server
)
Figure 3.1: Queuing system [1].
Little's law is general and could be applied in different systems. For example, Little's law could be applied in a production system where it relates the work items' flow time, throughput and the level of WIP by Eq. (3.2) [1]
Where WIP=average number of work items between start and end of production system TH=throughput rate of work items (which is assumed to match the arrival rate) FT=average flow time of work items
Little's law applied at the production system is similar to its original form. However, there is a distinct difference. The original Little's law is using the arrival rate of work items. On the other hand, Spearman et. al. used the departure rate (throughput) of the system [2]. It is more meaningful to use throughput as it is often a measure of the system performance.
3.2 Push and pull production system
In a push system, a production release date is calculated by taking into account the time
planned for production, shipping and other operations. Once these orders are released into the production system, they are pushed to the end of the system. As such, an upstream process would produce work items without considering the situation at the downstream process. This might build up the WIP unknowingly. Thus, in a push system, the throughput is controlled and the WIP (and flow time) is used as a performance measure
[3]. In a pull system, the work item cannot move downstream without authorization. The
work item would be pulled downstream when the downstream process gives a signal to the upstream. Thus, in a pull system, the WIP is controlled and the throughput is a performance measure [3].
3.2.1 Material and information flow
In the push system, the work items flow is in the same direction as the information flow [4]. The information in this case could be a master production schedule where the work items are produced according to predefined due dates. In the pull production system, the work items flow is in the opposite direction as the information flow. The information flow in this case would be a signal from the downstream process that the work item is ready to be produced downstream. Figure 3.2 show the information flow in the push and pull system.
Work items flow
Push System
M7)
(
Information flow
Work items flow
Pull System
Information flow
Figure 3.2: Material and information flow in a push system and pull system [4].
3.2.2 Control of WIP and throughput
Spearman et al. discussed that a pull system is relatively easier to control as compared to a push system [5]. WIP would be easier to control than throughput in practice as WIP could be observed in a straightforward manner. In addition, capacity estimation of the plant is required when throughput is the parameter to be controlled as in the push system. However, the capacity of the plant is difficult to estimate as it is subjected to many variations. These variations includes worker efficiency, machine breakdown and setup time. The orders could exceed the perceived capacity and cause the WIP to build up. The building up of WIP would be aggravated when seeking high utilization is of importance.
3.3 Kanban system
Kanban system is a type of pull production system where there is a set of kanban cards
circulating between each pair of buffer and the upstream machine [6]. These kanban cards are localized and not transferred along the entire line. When a work item has become a finished good, the kanban card is returned to the immediate upstream machine to signal that it has the authority to process one more work item. This relationship is the same throughout the line. Figure 3.3 illustrates a kanban system. Thus, the demand propagates up the production line. The machines will stop processing when the buffer is full. On the other hand, they will continue to process when the buffer is not full.
-Although kanban helps to reduce the WIP, it cannot be used under some environments. Kanban would not be useful when [5]:
1) The setup time is long
2) The scrap loss is high
3) The demand has large and unpredictable demand
M - B M -* B M -*G
Figure 3.3: Kanban system [6].
3.4 CONWIP system
CONWIP system is different from kanban system. There is only one set of cards that circulates around the entire line [6]. When a work item has become a finished good, the card is returned to the first machine to signal that it has the authority to process one more work item. The new work item would then be processed down the line like a push system. As the card is always transferred to the first machine, the WIP in the system should always be a constant number, assuming that the first station is never starved. A CONWIP system is shown in figure 3.4.
M FrB 34 M W B Msytm
Figure 3.4: CONWIP system [6].
3.4.1 Number of cards
CONWIP is easier to control and less complex than kanban as there is only one set of cards as compared to having one set of cards between each pair of adjacent processes in the kanban system [3]. There are more set of cards to be determined on the line in the
case of the kanban system. Since the number of cards in the system might need continuous adjustments over time, a kanban system is harder to control and maintain. However, the number of cards used in a CONWIP system can be more than that in a kanban system. Thus, the WIP level is likely to be higher in a CONWIP system. This implies that the cycle time is higher for the case in CONWIP system.
3.4.2 Stress level of workers
Spearman et. al. has also pointed out that a CONWIP system is less stressful to the production workers as compared to the kanban system [3]. There would be more pacing stress in the kanban system as the upstream workers need to replenish the void in the system to prevent the starvation of downstream machine. On the other hand, the workers in the CONWIP system experience less pacing stress as CONWIP acts as a push system at any machines other than the first one.
3.5 Simulation
It is possible to obtain analytic solution when the problem of interest is simple. However, many real life problems are complex. Simulation is useful in problems that are too complex to be evaluated analytically. It is more cost effective to carry out simulations to determine the suitability of the proposed plan as compared to experimentation with the real system. The simulation allows the user to have an insight on the performance of the plan. Simulation models could be static or dynamic. A dynamic model would be more applicable here as the production line evolves over time. Discrete event simulation is a model where it is dynamic, discrete and stochastic. Computer package that provides discrete event simulation includes Arena, ProModel and Simul8. Averill et. al. has proposed the following steps in a simulation modeling that would help in modeling a system [7]. These steps are shown in figure 3.5.
CHAPTER 4: METHODOLOGY 4.1 Problem solving phase
The author proposed 6 problem solving phases to meet the 3 objectives stated in chapter 2 of the thesis. The phases are shown in figure 4.1. Phase 1 introduces the production line proposed by the author. Different aspects of the proposed production line are discussed in this phase. Phase 2 involves the building of a simulation model of the proposed production line. In phase 3, a model of the current production line is created to act as a form of verification. In phase 4, three alternative configurations are tested for each line to find a suitable system for CAS. An improvement analysis is done in phase 5 to measure the performance of the proposed system. In phase 6, the author proposes the production line and makes recommendations to CAS.
Pha,-se I
Des(in prIopiosed pr-oductOio
P ase 2
Veif1ication1 using( Model Of current piroduction1 line
Pl ase 4
Collnpare- alterna~tive system1 conlfigur-ations
Pha'.se 5
lIiimos etet anial ,s s Phai~se 6
P -opose sOtolto
4.2. Design proposed production line
4.2.1 Changes to current production line
The author proposed to make three major changes to the current production line to meet the objectives outlined in chapter 2. These changes are:
e Use of dedicated production lines
* Change to pull production system * Align production to takt time
4.2.1.1 Dedicated production lines
The current production system is a mixed flow line where the products can flow to almost any downstream work stations. However, some work stations are unable to process all of the products. The products that could be processed by each work station are shown in table 4.1. A shaded box means that that product could be processed by that work station. For example, L22 could process both juice and milk products while L21 could only process juice products. The planner in CAS has to plan the route of the products during each production cycle to ensure that there are no clashes between the product routings and the work station capabilities.
Table 4.1: Work station capabilities. Products P13 P18 L21 L22 S52 S53 S54 S55
Juice 567
Juice 350
-In order to reduce the complexity of the current production line, the author proposes to split the entire line into two dedicated production lines A and B as shown in figure 4.2. The allocation of products between the two lines is explained in greater detail in section 4.2.3. There are several motivations to use dedicated production lines over the mixed
flow production lines:
e The lines are simpler to manage by CAS.
* There is more visibility of the products flow and decisions are made faster. e Any rush orders inserted into line A does not affect line B and vice versa.
e Planning lead time during each production cycle is reduced because planning
should be simpler.
Figure 4.2: Dedicated production lines.
One slitter (S54) is assigned to line A while three slitters are assigned to line B. This is due to two reasons. Firstly, the demand assigned to line A is less than that of line B. Secondly, only 5 and 9 web products are assigned to line A while 5, 7, 8 and 9 web products are assigned to line B. The setup time for changing of webs at the slitters is 60 minutes. Since there is more type of webs on line B, frequent setups are expected and the capacity of the slitter is taken up by these setups. This situation would be aggravated when rush orders of different webs are inserted after the production cycle has started. The number of setups is reduced by dedicating slitters to slit only products of 1 or 2 web types. S54 and S55 are assigned to slit 5 and 9 webs products. S53 is dedicated to slit 7 webs products and S52 is dedicated to slit 8 webs products. The advantage of the assignment on S54 and S55 is that when either S54 or S55 experience unexpected and prolonged downtime, products could be switched from one slitter to the other without disrupting other products on either line A or line B.
There are 14 doctoring work stations in CAS. 4 Doctoring work stations are assigned to line A while 7 doctoring work stations are assigned to line B. This is because line B has a higher demand and this is explained in the later sections. Thus, the defects on line B are higher and more doctoring work stations are required. The remaining 3 doctoring work stations act as backup for either of the line.
4.2.1.2 Pull production system
The current production system is a pure push production system. Orders are released into the production line through P13 or P18 when the printers have finished processing the previous roll. The current production system does not consider the status of the downstream work stations. Orders are still released to the printers into the production line even when the downstream work stations are stopped for a prolonged period of time.
A CONWIP pull production system is able to react to the actual situation in the
production line and allow CAS to have a better control over the WIP. There are several advantages of CONWIP production system over the current push system.
* Orders are not released into the system when the WIP has reached a predefined level using CONWIP cards.
* The total WIP in the production system stays relatively constant.
* The lead time to customers could be better estimated when the WIP stays at a near constant level.
Figure 4.3 shows a schematic of the pull production system proposed by the author. There are separate queues in each of the dedicated lines just before the printers. An order is released into the production line when there are available cards at the entry point. As
CAS has a large production floor area, a physical card is not appropriate to be attached to
each of the roll. CAS has initiated a concurrent project where radio frequency identification is used to track the rolls in the production line. When a roll leaves the end of the line (palletizer), a signal is sent back to the queuing area and authorizes that a new roll can be released into the production line. The products in line A go through the following path:
P13 -+ L21 -> S54 -> D1 to D7 (only defective products) -> Pal
and the products in line B go through the following path:
Conwip card 53 7 B web D5 to D11 P18 L22 S52we 8 & 9web Conwip card
Figure 4.3: Pull production system with card return.
4.2.1.3 Takt time
The current production line utilizes all the work stations at their maximum rate to increase their OEE. When a sufficient WIP buffer has been built up, the work stations are made to rest. The author proposes that the work stations rate should be aligned to the takt time of the demand during each production cycle. This implies that the work stations do not process the rolls at their maximum rate. When the demand is high, all work stations operate at a high rate and vice versa. The takt time for a given week for line A and line B is found using Eq. (4.1)
Takt time (mins/roll) = Total time in production cycle (mins)-Time loss (mins) Demand per week(roll) Eq. (4.1)
Net avaliable time (mins)
Demand per week(roll)
The total time in each production cycle is the same. Each production cycle comprises 7 days or 10,080 minutes. The time loss comprises planned maintenance, setups and other types of stoppages that can be anticipated or expected. The time loss is estimated from past data in CAS internal P2 system. The net available time for each work station is
... ... ... ... .... ... ... ... ... ... - 1- 1- ,
different as their time loss is different. The demand in the denominator of Eq. (4.1) is the demand in a week (one production cycle) expressed in rolls. Rush orders are not considered in the models due to two reasons. Firstly, the percentage of rush orders is small. Secondly, CAS is currently working on a customer order management project to minimize the occurrence of rush orders.
The doctoring work stations and palletizers do not have any planned maintenance, setups and other types of stoppages. Thus, their net available time is the total time in each production cycle. The number of doctoring work stations required on each line is different. 24% of the rolls on each line contain defects and require doctoring. The number of doctoring work stations is determined by Eq. (4.2)
Number of doctors = Process time (mins) + Net avaliable time (mins) Eq. (4.2) Demand require doctoring per week(rolls)
Number of doctors = Process time (mins) + Net avaliable time (mins)
Demand per week(rolls)x Defects (%)
The takt time for each of the work station is shown in table 4.2. The takt time required for the doctoring work stations are much slower than the rest of the work stations as only 24% of the rolls on each line contain defects and are directed to the doctoring work stations. A doctoring work station takes 392 mins (standard deviation of 72) to rework a roll. It is found that line A requires 4 doctoring work stations and line B requires 7 doctoring work stations. Thus, 11 doctoring work stations are required for the entire production line. This is the same as the number of doctoring work stations in the current production line. This leaves 3 doctoring work stations unused and assigned as backup. This assignment of the doctoring work stations is based on the assumption that the percentage of defects on each line remains at 24% regardless of the assignment of products on each line. CAS has to do further analysis to determine whether there is a correlation between product type and the percentage of defects.
Table 4.2: Takt time of work stations.
Line A
Net avaliable time Rate required Capacity Work station (mins per week) (mins/roll) (mins/roll)
P13 6,498 15.8 9.2
L21 9,491 22.9 12.8
S54 (5 & 9 web) 5,523 13.3 6.8
Doctoring (4) 10,080 101.3 392 per station
Pal 10,080 24.3 8.3
Line B
Net avaliable time Rate required Capacity
Work station (mins per week) (mins/roll) (mins/roll)
P18 6,408 9.3 9.2
L22 9,545 13.9 9.2
S52 (8 web) 7,269 10.6 5.4
S53 (7 web) 7,623 11.1 7.5
S55 (5 & 9 web) 7,078 10.3 4.5
Doctoring (7) 10,080 61.1 392 per station
Pa2 10,080 14.7 8.3
4.2.2 Selection of demand
Table 4.3 shows the demand of the first three months in 2010. CAS has estimated that the future demand would increase by 12% a year. The demand of March 2010 is 4461 rolls and this is the highest among the three months. Thus, the demand of March would reflect the future demand better. As such, the author chose the demand of March for the modeling of the production system.
Table 4.3: Demand of first three months in 2010.
Month January February March
Week 1 2 3 4 1 2 3 4 1 2 3 4
Weekly
demand (rolls) 747 1019 987 771 1003 798 1505 674 900 1142 1177 1242
Monthly total
The author excluded products that have infrequent and low demand in order to simplify the problem. These products account for 1.2% of the total demand, so it would not have a big impact on the accuracy of the model. The demand breakdown of all the products used in the modeling is shown in table 4.4. The products are differentiated by two codes. The lamination code is juice or milk. The size codes are numbers such as 465 and 350. The lamination and size code together would form a product, for example Juice 465.
Table 4.4: Demand breakdown of March 2010.
Products Wk 1 Wk 2 Wk 3 Wk 4 March Juice 465 368 359 352 1079 Juice 350 89 132 87 181 489 Juice 811 31 58 89 Juice 813 95 243 258 173 769 Juice 466 13 98 48 57 216 Juice 565 291 131 136 172 730 Juice 460 7 17 81 67 172 Juice 560 80 15 32 94 221 Juice 585 86 83 71 240 Juice 600 8 2 39 49 Milk 465 87 37 11 28 163 Milk 460 78 16 32 8 134 Milk 702 8 16 24 Milk 811 9 20 ___ 29 Total (rolls) 882 1142 1138 1242 4404
4.2.3 Products allocation
The capacity on each line is determined to ensure that the weekly demand does not exceed the capacity of line A and line B. The bottleneck (based on work station rate) of each line is at the laminating stage. Table 4.5 illustrates the maximum rate of each work station. The maximum rate on line A is 430m/min while the maximum rate on line B is 600m/min. The doctoring work stations and palletizers have a higher capacity than the printers, laminators and slitters.
Table 4.5: Maximum rate of work stations.
Line A Line B
Work station Maximum rate (rn/min) Work station Maximum rate (m/min)
P13 600 P18 600
L21 430 L22 600
S54 1000 S52 1000
S53 800
S55 1200
CAS has estimated that the maximum daily output of L21 and L22 is 80 rolls and 110
rolls respectively. The total time in a day is 1,440 minutes and the average length of a roll is 5513m. The processing time, based on the maximum capacity of 430m/min (L21) and 600m/min (L22), is 12.8 minutes per roll and 9.2 minutes per roll, respectively. CAS estimates that there is a capacity loss of 30%. This capacity loss includes setups, trial runs, break downs, short stops, rush orders and others. Thus, the available time per day is 1,008 minutes (70% of 1,440 minutes). The maximum daily output is found using Eq. (4.3)
Maximum daily output = Available time per day (mins) Eq. (4.3)
Fastest processing time (mins)
1,008
Maximum daily output of L21 or line A =128 78.75 ~ 80 rolls per day 12.8
1,008
Maximum daily output of L22 or line B = 1 109.57 - 110 rolls per day 9.2
Thus, the weekly capacity of the two lines A and B are 560 rolls per week and 770 rolls per week respectively. As such, the demand allocated to each production line must not
exceed this capacity.
The initial assignment of products to each line is based on the maximization of the number of flying setups on line B. The setup time and setup cost is minimized by maximizing the number of flying setups on line B. Table 4.6 illustrates the demand breakdown of every product and their allocation on line A and line B based on the initial assignment. The demand on line B is within the capacity of the line. However, the demand on line A has exceeded the capacity of the line in three of the weeks. The capacity of line A is 560 rolls a production cycle, but the demand for week 2, 3 and 4 is more than 700 rolls.
Table 4.6: Products allocation based on initial assignment.
Line A Line B
Products Wk 1 Wk 2 Wk 3 Wk 4 March Products Wk 1 Wk 2 Wk 3 Wk 4 March
Juice 465 368 359 352 1079 Juice 466 13 98 48 57 216 Juice 813 95 243 258 173 769 Juice 565 291 131 136 172 730 Juice 350 89 132 87 181 489 Juice 460 7 17 81 67 172 A Total 184 2337 Juice 560 80 15 32 94 221 Juice 585 86 Juice 600 8 Juice 811 31 83 71 2 39 58 240 49 89 Milk 465 87 37 11 28 163 Milk 460 78 16 32 8 134 Milk 702 8 16 24 Milk 811 9 20 29 B Total 698 399 434 536 2067 A & B Total 882 1142 1138 1242 4404
