APPLICABILITY OF WEBCAMS TO INVENTORY CONTROL

OF TECHNICAL WHOLESALE ITEMS

Erno Salmela and Ari Happonen

Department of Industrial Engineering and Management, Lappeenranta University of Technology

P.O. Box 20, 53851 Lappeenranta, Finland

Keywords: Webcam, inventory control, supply chain management.

Abstract: This study aimed to determine whether webcams could be applied to the operative and tactical inventory

control of technical wholesale items for which customers do not keep track of the inventory balance. The

study was conducted as a ten-case study in Finnish industry with machinery industry companies as the

customers and technical wholesalers as the suppliers. Even though none of the cases used webcams in their

inventory control, the research results indicate that that webcams could be suitable for the purpose

particularly in operative order-delivery process. However, webcam systems are considerably more

challenging to apply to tactical inventory control.

1 INTRODUCTION

The research was conducted as a ten-case study in

Finnish industry with machinery industry companies

as the customers and technical wholesalers as the

suppliers. The studied cases generally apply the

VMI (Vendor-Managed Inventory) model, which in

this research refers to inventory replenishment

carried out by the wholesaler, who delivers items to

shelf spaces in the customer’s production facilities

or warehouses in accordance with the management

model agreed on. The management model is

typically based on a number of control parameters,

which include the lot size, order point and delivery

frequency (Salmela et al. 2007).

Some of the studied cases utilized the CMI (Co-

Managed Inventory) model. In the CMI the

customer maintains a forecast and distributes it to

the supplier, which means that some degree of

management and responsibility is on the customer

side. According to Seifert (2003), VMI is mostly

based on warehouse levels and sales data, but not on

forecasts – which makes CMI different from VMI.

Technical wholesale items (e.g. nuts and bolts)

are typically standardized low-cost products with a

constant demand and a rather short supply chain.

Nonetheless, some of the items play a critical role

because their absence may bring the entire

production line to a halt. Common ways of avoiding

such shortages include large storage buffers and

frequent inventory checks (Salmela et al. 2007).

Technical wholesale items usually include

mechanical, electrical and hydraulics items used in

production and maintenance. Customers usually

keep track of the inventory balance of electrical

equipment, which means they have records of them

in their inventory systems. This enables the use of

automatic and real-time control and order methods

for these items. In contrast, customers' inventory

systems rarely include records of the inventory level

of mechanical and hydraulics items (Salmela et al.

2007). These items are the particular focus of this

study

Transparency of information is needed in the

VMI and CMI models. In transparent supply chain,

the decision maker has all the information needed to

make decisions (Otto, 2003; Gaonkar and

Viswanadham, 2003). In this research, the

applicability of webcams is studied to improve

decision making and transparency of information in

the studied supply chains.

The VMI includes tactical and operative level

tasks, information and decisions. At the tactical

level, the main task is to adjust the control parameter

values to correspond to item consumption. The

consumption history data and demand forecasts are

utilised to perform this task. In practice, the

parameter value adjustment is done at the

commissioning stage of the item (e.g. during the first

488

Salmela E. and Happonen A. (2008).

APPLICABILITY OF WEBCAMS TO INVENTORY CONTROL OF TECHNICAL WHOLESALE ITEMS.

In Proceedings of the Fourth International Conference on Web Information Systems and Technologies, pages 488-490

DOI: 10.5220/0001518504880490

 SciTePress

six months), after which parameter adjustment is

sporadic or non-existent. Usually, parameters are

adjusted after the commissioning period only if

shortages occur repeatedly or if the customer

anticipates significant changes in demand. The low

frequency of adjustments can be explained by the

large amount of manual labor it requires, which

results in costs higher than the expected profits

(Salmela et al. 2007).

In operative level order-delivery process,

wholesalers assess the customer’s replenishment

needs in connection with each replenishment visit.

The replenishment need is normally based on a

visual assessment of the inventory level. Rapidity is

of the essence because the customer site may contain

hundreds of shelf spaces. Due to the time constraints

and visual checks, the assessment is not very

precise. However, accuracy is not even necessary for

the items in question due to wide safety margins.

When inventory levels are below the order point, the

wholesaler’s representative normally records the

need for replenishment and later enters the

information into the wholesaler’s system. Different

methods were used for records and information

transfer in different cases. For instance bar codes

and laptop computers were used for recording

replenishment needs, and remote access in

transmitting the information in a batch run to the

wholesaler’s order system (Salmela et al. 2007).

Orders were typically entered into the

wholesaler’s order system at the end of

replenishment day, or on the following day, at the

latest. Normally, the studied cases exhibited no need

for more real-time information transmission because

the picking and delivery processes applied would

have had no use for information sent any sooner

(Salmela et al. 2007).

2 FINDINGS

A webcam system could be applied to the operative

order-delivery process of technical wholesale items

with no customer records on inventory balance.

Webcams would be best suited to remote monitoring

of large items, allowing the inventory levels to be

assessed based on the picture. However, technical

wholesale items are mainly small in size, which

means some kind of visual signal would be

necessary to indicate that the inventory level is

below the order point and that a replenishment

decision needs to be made.

Our research involved laboratory-environment

modelling of an industrial shelf with tilted boxes.

Labels indicating the order point were fastened on

the bottom of the boxes. After this, pictures were

taken at different distances and in different lighting

conditions. The results of the laboratory tests were

positive, i.e. technically, the webcam system is

suitable for remote monitoring of small technical

wholesale items. The items should roll or slide down

easily in the tilted boxes as the inventory level

decreases. Alternatively, the boxes should be at such

a great angle that sliding is inevitable as the

inventory level drops.

Merely seeing the order point label in the

webcam picture is not enough to make a

replenishment decision because the items cannot be

identified from the pictures. The identification

would require documentation on the shelf location of

the items. This information could be on a separate

document or pasted as layered information on the

picture taken by the camera. Furthermore, manual

work is needed to adjust order point parameters,

because the labels fastened on the bottom of the

boxes must be manually moved.

In addition to replenishment decisions based on

remote monitoring, the webcam system could be

applied to the management of extensive and rapid

changes in consumption by comparing two

consecutive pictures to each other. Especially

overtime work may increase the customer’s

consumption significantly, and pictures sent to the

supplier daily would provide information on these

kinds of changes.

The simplest technological solution would be for

the webcam to email pictures directly to the supplier.

This could be applied to cases where the number of

pictures is low and/or pictures are sent at low

frequencies. As the number of pictures increases,

some kind of application (e.g. for recording,

searching and filing pictures) is needed to manage

the order-delivery process.

The webcam system helps to increase the

efficiency of operative order-delivery process

through remote monitoring and replenishment

decisions. The system cannot, however, be used for

automatic control parameter adjustment at a tactical

level because it does not provide arithmetic

information on the inventory balance and on the

consumption of the items. In the absence of

inventory balance information, the consumption

history cannot be analysed and control parameters

cannot be adjusted automatically.

APPLICABILITY OF WEBCAMS TO INVENTORY CONTROL OF TECHNICAL WHOLESALE ITEMS

489

3 CONCLUSIONS AND FUTURE

RESEARCH

A webcam system can help in improving the

efficiency of an operative order-delivery process,

whereas in tactical inventory management,

automatic control parameter adjustment would result

in excessive costs compared to the profits, or be

altogether unfeasible. Tactical gains could be

achieved with a system of scales or by including the

items in inventory accounting in the inventory

management system (Happonen & Salmela, 2007).

A webcam-based solution can be applied to

inventory control only in certain type of supply

chain environment. The fundamental requirement

for applying a webcam-based solution is that the

wholesaler has no information on the customer’s

inventory balance. Below are some additional

arguments for adopting a webcam system:

• The number of items is low, which would

allow for a webcam system which requires

manual labor (e.g. browsing pictures is a

slow task).

• When consumption is low, the

replenishments of items and the inventory

level checks are infrequent.

• The consumption of items fluctuates (e.g.

maintenance items).

• The customer is logistically far away,

which makes frequent replenishment and

inventory inspection visits unfeasible due to

the related labor and travel expenses.

• The customer does not want to the

wholesaler's representative to make

inventory inspection visits to the

plant/warehouse for instance for

information security reasons.

• The facilities are difficult to inspect in

person (e.g. high-rise warehouses).

• The lighting conditions in the

plant/warehouse are quite good.

• The replenishment limit can be identified

from a photograph.

• The physical characteristics of the item

allow it.

The advantage of the webcam system is its

simplicity and low commissioning costs compared,

for instance, to a scale system. On the other hand, its

disadvantages are that its use is limited to the

operative level and it still requires manual labor.

Further research is necessary on the

incorporation of pattern recognition and shelf space

coordinate features into the system. For example, a

pattern recognition function could automatically

identify the label at the bottom of the box, indicating

the need for replenishment. Shelf space coordinates

would allow connecting items to specific shelf

spaces. Connecting the replenishment need and item

identification information would enable placing fully

automated replenishment orders directly into the

wholesaler’s system.

REFERENCES

Gaonkar, R. and Viswanadham, N. 2003, “Robust Supply

Chain Design: A Strategic Approach For Exception

Handling”, Proceedings of the 2003 IEEE, Internation

Conference on Robotics & Automation, Taipei

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Happonen, A. and Salmela, E. 2007. IT-solutions as a Part

of Forecasting and Proactivity in Supply Chains.12th

ISL (The 12th International Symposium on Logistics),

08. – 10.07.2007. Budapest.

Otto, A. 2003. ”Supply Chain Event Management: Three

Perspectives” In: International Journal of Logistics

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Salmela, E., Happonen, A. and Hämäläinen, H. 2007.

Kollaboratiivisen yhteistyön soveltuvuus teknisten

tukkukauppanimikkeiden toimitusketjuun

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Salmela, E. and Happonen, A. 2007.Applicability of

CPFR on Inventory Replenishment Operation Model of

Low-value Items. Finnish Machinery Industry - Case

Study. 12th ISL (The 12th International Symposium

on Logistics), 08. – 10.07.2007. Budapest.

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