Assembly AutomationMaterials flow improvement in a lean assembly line: a case studyRosario Domingo Roberto Alvarez Marta Melodía Peña Roque Calvo

Article information:To cite this document:Rosario Domingo Roberto Alvarez Marta Melodía Peña Roque Calvo, (2007),"Materials flow improvement in a lean assemblyline: a case study", Assembly Automation, Vol. 27 Iss 2 pp. 141 - 147Permanent link to this document:http://dx.doi.org/10.1108/01445150710733379

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Research article

Materials flow improvement in a lean assemblyline: a case study

Rosario Domingo

Department of Manufacturing Engineering, National Distance University of Spain (UNED), Madrid, Spain

Roberto Alvarez and Marta Melodıa PenaDepartment of Industrial Engineering, Antonio Nebrija University, Madrid, Spain, and

Roque CalvoDepartment of Manufacturing Engineering, National Distance University of Spain (UNED), Madrid, Spain

AbstractPurpose – This paper seeks to analyse the internal materials flow in lean manufacturing in an assembly line of the Bosch factory, located in Spain. Theobjective is to develop a handling system in a small space, capable of solving the problems of accumulated intermediate stocks of parts. Animprovement is proposed adopting the milkrun handling system, while verifying the advances by means of lean metrics.Design/methodology/approach – Based on this case study, the paper identifies data from value stream mapping and uses lean metrics, such asdock-to-dock time and lean rate. The case study develops a timetable and routing analysis for the milkrun to improve materials flow.Findings – The proposed logistics allows an improvement of lean metrics, without modifying the layout and production planning. The routing flexibilityof the milkrun reduced stocks, work-in-process and dock-to-dock time, while increasing lean rate.Research limitations/implications – The findings are limited due to the focused nature of the case study. Although the solution is designed for aparticular plant, the methodology is fully exportable.Practical implications – The paper shows a real case study illustrative for systems management. This research shows significant benefit associatedwith the implementation of lean programs.Originality/value – It details how the application of lean manufacturing tools could necessitate a study of materials handling to improve lean metrics.

Keywords Lean production, Assembly plants, Materials handling equipment

Paper type Case study

Introduction

Lean manufacturing focuses on reducing waste and non-

value-adding activities (Womack et al., 1990), and includes

forms of just-in-time (JIT) strategy. The waste can be

overproduction, defects, unnecessary inventory, inadequate

processing, excessive transportation, waiting and unnecessary

motion (Womack et al., 1990). Firms measure their degree of

commitment to lean production via total quality management

(TQM) and JIT programmes (Soriano-Meier and Forrester,

2002). However, the implementation of lean management in a

manufacturing system is a complex task. Lean manufacturing

systems are designed for a smooth demand. However, some

degree of flexibility is necessary to cope with uncertainties,

and this might include a variable number of kanbans, set-up

reduction through single minute exchange of dies, and the

layout of machines in flexible workstations. Layout and

kanban system play an important role in materials flow.In manufacturing plants, the assembly areas usually

maintain a store of components to be assembled in the

finished part. The main problem associated with the supply of

these components is the limited space of the workstation,

optimising the overall production-shop layout. This could

mean that the quantity of components stored in the workplace

does not cover the daily production requirement.

Consequently, it is important to replace the consumed

material at convenient time intervals, to keep the assembly

line running. However, the improvement process of

synchronous production (Womack and Jones, 1996) is

creating problems with internal transportation of materials

to the assembly workstations, and collection and storage of

finished product.Shah and Ward (2003) found that the influence of lean

practices contributes substantially to the operating

performance of plants. However, the implementation

requires customised solutions. The internal materials flow to

and from each workstation depend on the production

conditions and particular characteristics of each workplace.

The work-in-process must be as reduced as much as possible.

The immediate requirements are problems solution and a

The current issue and full text archive of this journal is available at

www.emeraldinsight.com/0144-5154.htm

Assembly Automation

27/2 (2007) 141–147

q Emerald Group Publishing Limited [ISSN 0144-5154]

[DOI 10.1108/01445150710733379]

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fluent flow, balance and synchronization, and a shorter cycle

time. For this, routing flexibility is a key factor. Routing

flexibility is defined by Sethi and Sethi (1990) as the ability to

produce a part by alternative routes through the system.

Although this routing flexibility can be achieved by means of

machines, we take routing flexibility to mean the versatility of

material handling systems of Sethi and Sethi (1990).

Moreover, according to Lejtman et al. (2002), the design of

the routing requires an evaluation of the entire loaded and

unloaded handling system for a given shop layout for efficient

material flow. In lean manufacturing, material handling

systems must contribute to synchronous materials flow.Different authors have studied these problems, and the

literature includes many papers related to the routing problem

and its mathematical solutions. These include items such as

the assessment of routing flexibility (Calvo et al., 2006),

transporter routing models (Hwang, 2004) or sometimes

routing of milkruns (Du et al., 2006), but not directly related

to lean manufacturing. However, a lean approach has the

added advantage that it allows the use of easily applied

industrial tools. A tool used to identify where waste occurs is

value stream mapping (VSM). The literature shows examples

of its utilization in other fields (Sullivan et al., 2002), althoughthey do not deal with materials handling.The objective of this paper is to standardise materials flow

in a reduced floor space through materials handling, to show

the relationship between routing flexibility and performance

in a lean assembly line. In this paper, we use a case study in

the context of lean production implementation. The study,

accomplished by the authors, is part of a broader project

related to the application of lean manufacturing tools in a

Bosch factory, located in Spain. The case analyses the internal

materials flow in the assembly line. First we describe the

research approach. Next, the paper describes the existing

materials flow in the manufacturing process. After that, we

analyse the new materials flow. Finally, some results are

discussed and conclusions are drawn.

Research approach

The research approach is based on a case study. A detailed

study of the assembly line is carried out for a particular

company. It is the assembly line of combustion injection

valves of in the Bosch GMB factory in Alcala de Henares

(Madrid), following the Bosch Production System

methodology. This methodology includes a pull system,

Total Productive Maintenance and kanban system. The plant

has adopted lean manufacturing principles, for both the

supply system and for stock control. However, there are some

problems in the supply to the lines:. The available storage space in the assembly workplaces is

insufficient, originating from a global shop layout

optimisation, and the number of components held does

not cover the daily consumption.. Operators must walk out of their workplaces to replace

material.

This contributes to a lower productivity and a poorer

synchronization between different workplaces.A study of the assembly line has been carried out using the

tools of lean manufacturing:. collecting the data during the time horizon (that is the

months of March, May and August);

. VSM application to help understand and streamline the

work processes; and. analysis of data according to lean metrics.

Although the paper focuses on the improvements carried out

in May, we also consider the situation in March, because

during the period March-May the following tasks were

accomplished: modification of layout and kanban

implementation. These actions have worsened the

intermediate stocks and handling times, even when final

stock was reduced. VSM is a visualisation tool for identifying

and eliminating the waste and improving the materials flow

(Womack and Jones, 1996; Sullivan et al., 2002). VSM was

deployed in March, May and August. On the other hand, the

literature on lean manufacturing presents metrics studies such

as those of Martınez and Perez (2001), Pavnaskar et al. (2003)

or Agarwal et al. (2006), which yield metrics to define lean

manufacturing. For this reason we have adopted the typical

indicators in these systems. Consequently, the metrics of lean

manufacturing to consider are: stocks of parts, stocks in

intermediate warehouse, dock-to-dock time, lean rate. These

are adequate for this situation. Dock-to-dock time is the time

the product spends from reception in plant to delivery or

shipping, excluded the storage time. Lean rate is the relation

between value-added time and the time the product spends in

the plant from when it enters until it leaves.The solution to the problem is a reordering system,

established across the production line to a fixed timetable and

with a defined path, picking up any empty packages, and

supplying full packages to the same point. This system can be

a transport system for the horizontal movement of materials,

such as an automated guided vehicle, container or conveyor,

appropriate to the needs of each production area and to the

volume of parts to be transported. The adopted solution is

not usually automation. According to Coffey and Thornley

(2006) in lean assembly plants, the current priority is to

manage the manual part of the process. When the vehicle

travels the path, if there are no parts to pick up or supply, then

the vehicle continues on its programmed route.This supply system is called the milkrun, because it is a

production system similar to that used in small supermarkets

with a fixed amount of shelf space; the operator takes the

necessary material for production and stocks the empty

packages after consumption. The supermarket’s capacity

must allow for material availability between two consecutive

runs, so that the operator does not stop working. In the

milkrun path, the empty packages are withdrawn. They are

not replaced until the following path of the milkrun, when it

restocks the material and withdraws any further empty

packages that it finds. Therefore, the objective of the milkrun

(helped by the kanban system) is to integrate the internal

supply of parts with the supply in the assembly area.

Existing materials flow

The product is a combustion injection valve called the EV6.

The basic component of an EV6 is the stem. The lower end of

the stem holds a conical-shaped cup, with an injection hole

drilled in its centre. Inside the stem is a needle, attached to a

ball that presses against the inside of the cup under spring

loading, to give a tight valve, as part of the engine. When a

current passes through the coil, the magnetic field pulls the

Materials flow improvement in a lean assembly line

Rosario Domingo et al.

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needle, compressing the spring. This is controlled by the

engine electronics.The main join technique of the EV6 is laser welding. This is

used in the stem, the needle and cup subassembly, and the

support fixtures. The casing of the subassembly of stem, coil,

supporters and adjustment sleeve, is injected with plastic. The

major process steps in manufacturing are illustrated and

described below. Figure 1 shows the existing manufacturing

processes. The washing machine 2 is repeated to show a linear

process and make it easier to understanding the order of

activities. All the component parts of the EV6 are received in

the production area, where they are stored until consumed.

From this point, all the parts undergo different processes

before they arrive for final assembly. Each is decontaminated,

demagnetised and washed (washing machine 2) before

assembly (Figure 1). The assembly process includes three

main subassemblies: the cup, the stem and the needle. These

parts are first received in subassembly workstations where

independent tasks are carried out.The subassembly has several stages, which are performed in

automatic and independent workstations. These workstations

are physically isolated and do not allow for continuous

materials flow. These stages are described briefly as follows:. Machining of cup. The contact area within the cup is

prepared to precise dimensions.. Assembly of cup. After washing, the cup is welded to the

plate which directs the combustion jet. The plate is a

particular part for each type of EV6.. Assembly of needle. The three parts are assembled by

welding. The needle assures the tightness of the cup.

. Assembly of stem. It is assembled with two tubular parts,

with an internal sleeve to adjust the characteristics of theEV6.

After each subassembly, a visual inspection is made to verifythat the parts are clean, without chips or damage. The cups

and needles are washed and introduced to workstation 5 of

the assembly line.Frequent lack of stock and changes of production plan

necessitate rushed-orders and repeated communication withsuppliers. However, sometimes parts or materials were not

delivered fast enough and at other times the production partsaccumulated for hours at some workstations. This downtime

and binge-inventory create no value, so the elimination ofeven a portion of that wasted time could create a huge

improvement. The positioning of machines and equipmentcreated unnecessary internal transport and intersecting

material flows. As a first solution, in a global project for thefactory, a kanban path was designed to improve the storage-

shelf control. Although the inventory has been reduced, someproblems related to materials flow continue. In the VSM done

during the month of March we noticed accumulatedinventory at different points. A critical point is workstation 5.

In this station parts accumulate for a waiting period of 32 hbefore utilization.

Designing the new materials flow

In the subassembly process of the valve parts, the company

decided to use a kanban system to assure a materials flowaccording to the pull system. These sub-assembled parts go to

the line for final assembly, as follows: different numbers of

parts are present at different workstations because the trayshave different capacities. Because of this, idle material

accumulates. There is insufficient control of internallogistics. The internal logistic problem cannot be tackled

just by mathematical programming. To get the correctreplacement of material it is necessary to use the milkrun,

and an efficient and effective standardized routing must bedetermined.Previously, a decision had been taken about the kind of

conveyor to use; this must run through the line without

interrupting the workers. This conveyor must have thecapacity to transport the trays between the workstations. The

layout was unchangeable due to a decision by the companyafter several studies of capacity, distances, speed and

manageability (Figure 2). The decision was that the bestmilkrun would be a conveyor with wheels handled by a worker

(Figure 3).To establish the route for the milkrun, it is necessary to

consider the following information:. The rate of consumption of material. This involves

calculating the speed of the assembly line.. The number of trays needed for each part.

Therefore, it is necessary to establish the number of milkrunroutings and the visit frequency to the workstations

(frequency of pick-up/delivery).This information is necessary to calculate the needs of each

workstation. The available storage shelf area for each of theseworkstations is known in advance. The data are: capacity the

storage shelves (trays), workstation capacity (trays), trayscapacity, spend per tray, visit frequency and stop points of the

milkrun to withdraw and reorder the material in workstations

Figure 1 Flowchart of production process

Materials flow improvement in a lean assembly line

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2, 5, 16, 14, cup subassembly, needle subassembly and stem

assembly. The speed of a tray is sufficient to produce

300 valves/h. The maximum visit frequency is one hour (at

7.00, 8.00, 9.00, 10.00, 11.00, 12.00, 13.00 and 14.00 on the

morning shift). Figure 2 shows the results of this study. Note

that the workstation labels are not in sequence since we have

used the existing labels of the Bosch factory.The pick-up and delivery points are shown in Figure 4,

which indicates the layout of workplaces in the shop. The

routing begins and ends in the assembly washing; so it is

necessary to establish the direction of routing. Note that the

turn-around point of the U-shaped route is movable. Then

the milkrun can begin. The sequence of operations is defined

in the layout.With this information the minimal frequency of the milkrun

is set. We also define different routings for different hours,

since it is not necessary to visit each job with a high frequency.

The routing is set according to Figure 5.This routing could change according to the needs of the line

because the process is flexible and in a state of continued

improvement. It is possible to increase or reduce the visit

frequency to workstations. The plan shows only the first shift,

Figure 3 Milkrun

Figure 2 Intermediate warehouses regulated by the milkrun

Materials flow improvement in a lean assembly line

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but is obviously applicable to any other shift. Figure 6 shows

the detailed scheme of milkrun paths around the different

workstations; it is a development of Figures 2 and 5.

Results

The verification of results was carried out during the months

of March and August. A VSM analysis was performed on the

cup, since it is the most critical part of the valve because it

covers the two machining operations and their respective

washings (Figure 1). The results are positive in terms of

inventories of parts in different key points. Metrics are

important to confirm the progress and identify areas for

further improvement. The lean rate is still large, and we

should strive to reduce it. It is useful to find and mark

inventory accumulations where the flow has to be interrupted

because of process problems.Lean rate is calculated by dividing added-value-work-time

by the dock-to-dock time. Dock-to-dock time characterises

the material flow through the value stream, the time it takes

for material to flow from the receiving dock (or order entry

point) to the shipping dock. It is thus, a measure of the ability

to deliver on time and is generally a good indicator of the

effectiveness of lean initiatives to improve the lean flow. It is a

reliable indicator of the extent to which inventories are being

reduced and cash flow improved (Womack and Jones, 1996).During the month of May the inventories were reduced by

1,195 parts, and in August the reduction was 456 queue

parts. This led to the reduction of idle times, from 32 to

10.9 h in August. The objectives were twofold: reducing

stocks while avoiding idle times or movements of workers due

to accumulated material. Both have been achieved. The

metrics of lean rate and dock-to-dock time, have been

improved. Dock-to-dock time is reduced from 19.75 days in

the March VSM to 10.7 days in August. At the same time,

lean rate is increased from 0.38 to 0.44 per cent.Improvements attributed to the milkrun began in May and

were measured in August. In this time (May-August), the

stocks total has been reduced from 17,303 parts to 16,020

parts, and stocks in the intermediate warehouse have been

reduced from 20 to 10.7 days, dock-to-dock time from 22.8 to

17.1 days, and lean rate has increased from0.33 to 0.44 per cent.

These are shown in Figure 7. Note that the milkrun effects

have improved three metrics. These metrics had not improved

Figure 4 Pick-up and delivery points in the routing of the milkrun

Figure 5 Routing of milkrun

Materials flow improvement in a lean assembly line

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Figure 7 Results from VSM

Figure 6 Detailed routing of the milkrun

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during the period March-May in spite of the implementationof a kanban system in the machining 1 stage.

Conclusions

This paper has introduced a real industrial case study ofassembly line improvement by means of lean management.The empirical results drawn from the case study serve todemonstrate that an operating decision has helped to improvethe lean metrics, in particular reducing the dock-to-dock timeand increasing the lean rate, and shows the transformation ofa former line manufacturing organization into a better leanorganization that has attained lowest cycle time. The milkrunreduces waste in terms of unnecessary inventories, excessivetransportation and idle times, without changing theproduction philosophy or layout. However, thisimprovement cannot be static and isolated, it is part of acontinuous improvement strategy. The advances will continuein the future. Therefore, in future researches, it will beinterested to develop a framework for modelling the practice.The combination of milkrun and VSM is an important tool

for routing flexibility increases and process improvement forany industry. Experience indicates that they are suitable,useful and practical tools for any company. Nevertheless,every factory is different and needs to adapt these tools to itsparticular manufacturing characteristics, layout, inventory,flow charts, and organization.

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Corresponding author

Rosario Domingo can be contacted at: rdomingo@ind.

uned.es

Materials flow improvement in a lean assembly line

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Volume 27 · Number 2 · 2007 · 141–147

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15. Yavuz A. Bozer, David D. Ciemnoczolowski. 2013. Performance evaluation of small-batch container delivery systems used inlean manufacturing – Part 1: system stability and distribution of container starts. International Journal of Production Research51:2, 555-567. [CrossRef]

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17. Ryspek UsubamatovSchool of Manufacturing Engineering, University Malaysia Perlis, Arau, Malaysia Abdul Rahman RizaSchoolof Manufacturing Engineering, University Malaysia Perlis, Arau, Malaysia Muhamad Nasir MuradSchool of ManufacturingEngineering, University Malaysia Perlis, Arau, Malaysia. 2012. A method for assessing productivity in unbuffered assemblyprocesses. Journal of Manufacturing Technology Management 24:1, 123-139. [Abstract] [Full Text] [PDF]

18. Huseyin Selcuk Kilic, M. Bulent Durmusoglu, Murat Baskak. 2012. Classification and modeling for in-plant milk-rundistribution systems. The International Journal of Advanced Manufacturing Technology 62:9-12, 1135-1146. [CrossRef]

19. ANIL GUPTA, T K KUNDRA. 2012. A review of designing machine tool for leanness. Sadhana 37:2, 241-259. [CrossRef]20. Anand GurumurthyMechanical Engineering Group, Birla Institute of Technology and Science, Pilani, India Rambabu

KodaliMechanical Engineering Group and Engineering Technology Group, Birla Institute of Technology and Science, Pilani,India. 2011. Design of lean manufacturing systems using value stream mapping with simulation. Journal of ManufacturingTechnology Management 22:4, 444-473. [Abstract] [Full Text] [PDF]

21. Bimal NepalDepartment of Engineering Technology and Industrial Distribution, Texas A&M University, College Station,Texas, USA Malini NatarajarathinamDepartment of Engineering Technology and Industrial Distribution, Texas A&MUniversity, College Station, Texas, USA Krishna BallaDepartment of Mechanical and Industrial Engineering Technology, Purdue

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University‐Fort Wayne, Fort Wayne, Indiana, USA. 2011. Improving manufacturing process for biomedical products: a case study.Journal of Manufacturing Technology Management 22:4, 527-540. [Abstract] [Full Text] [PDF]

22. Bhim Singh, Suresh K. Garg, Surrender K. Sharma. 2011. Value stream mapping: literature review and implications for Indianindustry. The International Journal of Advanced Manufacturing Technology 53:5-8, 799-809. [CrossRef]

23. Bhim SinghDepartment of Mechanical Engineering, Galgotia's College of Engineering and Technology, Greater Noida,India S.K. GargDepartment of Mechanical and Industrial Engineering, Delhi Technological University, Delhi, IndiaS.K. SharmaDepartment of Mechanical Engineering, National Institute of Technology, Kurukshetra, India ChandandeepGrewalDepartment of Mechanical and Manufacturing Engineering, Schulich School of Engineering, University of Calgary,Calgary, Canada. 2010. Lean implementation and its benefits to production industry. International Journal of Lean Six Sigma1:2, 157-168. [Abstract] [Full Text] [PDF]

24. Roberto Álvarez, Roque Calvo, Marta M. Peña, Rosario Domingo. 2009. Redesigning an assembly line through leanmanufacturing tools. The International Journal of Advanced Manufacturing Technology 43:9-10, 949-958. [CrossRef]

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