SMART TROLLEY APPLICATION REDUCE PICKING ERROR IN WAREHOUSE, SUPERSTORES AND SHOPPING CENTRES

“Measured in time and money – order picking is, without doubt, the most costly activity in a typical warehouse. It is also the activity that plays the biggest role in customer satisfaction with the warehouse – and in the final analysis the entire Supply Chain.” ——– **Professor René de Koster

Introduction

There are a lot of ways that Smart Trolley Application is helping us in the warehouse, superstores and shopping centers like, increased productivity, reduce labour costs, faster order fulfilment, Improve order accuracy, better stock rotation, enhanced Customer service, Real-time operational visibility and decision support system etc (Dematic Global Website, 2018). Productivity and Error rate is negatively related. The Lower the error rate is the higher the productivity is. In the following section, we will discuss how smart trolley system reduces picking error in the warehouse, superstores and shopping center.

Automated Picking Vs. Manual Picking System

In today’s fast-paced environment, manufacturer, and distributors are pressured to efficiently fulfill orders on time. In most cases, this leads to picking and staging orders prior to shipment, which impacts the entire supply chain process. Following table shows how automated picking can improve the entire supply chain process:

Automated Picking (Goods-to-Man)

Goods-to-Man is a modern method of order fulfillment. The product is moved directly to the operator, who can then pick what is needed to fulfill orders. It allows for an increase in efficiency and accuracy of the picking process.
Automated picking -short travel times, high picking rate, shorter lead times, improved service levels.
The ideal concept for fast moving consumer goods and where accuracy is critical.

Manual Picking (Man-to-Goods)

The most common type of picking in practice is manual picking based on the principle of man-to-goods. In picking systems like this the goods are usually provided statically on shelves. The order picker usually receives the process-relevant information in the form of a list.
low picking performance compared to automated picking solutions and the fact that humans make mistakes.
The ideal concept for slow-moving products in retail and wholesale distribution centers.

Types of Picking Methods where Smart Trolley Can be used

Methods are defined in terms of (a) pickers per order – the number of pickers that work on a single order at one time; (b) lines per pick – the number of orders a single item is picked for at one time; and (c) periods per shift – the frequency of order scheduling during one shift. Order Picking Methods Include:

Zone Picking: Order pickers are assigned a specific and physically defined zone in the pick area. The picker assigned to each zone is responsible for picking all of the SKUs located in the zone for each order. In the event that an order requires SKUs that are located in multiple zones, the order is filled after it passes through each zone. This is also referred to as the “pick and pass” methodology. In zone picking, there is only one scheduling period per shift. This means there is a cut-off point for orders to be queued into the order picking process and any order received after that cut-off point will get fulfilled during the next shift.

Batch Picking: Batch picking is when one picker picks a group, or batch, of orders at the same time, one SKU at a time. This is advantageous when there are multiple orders with the same SKU. When that occurs, the order picker only needs to travel to the pick location for that specific SKU once, in order to fill the multiple orders. The main advantage of choosing this method is the reduced travel time, which increases productivity. Batch picking is often used when the typical order profile has only a few SKUs (under four) and the SKUs physical dimensions are relatively small. Just as in zone picking, batch picking requires only one order scheduling window per picking shift.

Wave Picking: Wave picking is very similar to discrete picking in that one picker picks one order, one SKU at a time. The main difference is the scheduling window. In discrete picking, there is not a scheduling window whereas in wave picking there is. Orders may be scheduled to be picked at specific times of the day, which is usually done to coordinate and maximize the picking and shipping operations.

Types of Error

To err is human and order picking is not an exception. To conquer problems related to errors in order picking, use of technologies is a common phenomenon nowadays. This section will discuss the common types of Error made by pickers and shoppers. Also, this will justify why companies are moving from conventional / Manual Picking system (Person-to-Goods) to Modern / Automated Picking System (Goods to Person Picking system).

a. Types of Picking Errors in a Warehouse

The error rate of a conventional order picking system is on average about 0.26 %. This figure contains different types of picking errors. A distinction is made between the following types of errors:

Miss Pick: The wrong item is picked in addition to the correct item. Also, it can be the wrong item is picked instead of the correct item.

Wrong Quantity (Short pick or Over pick): The wrong quantity of items is picked which can be either too many or too few.

Omission Error: An order line item has been forgotten or an item is not picked at all. Sometimes the omission error is referred to a special case of the short pick error with the quantity 0.

Condition Error: An incorrect action was carried out on the product. Condition errors are often interpreted in different ways. Common examples are damaged products or improperly labeled articles.

b. Types of Picking Errors in Super Stores and shopping center

Besides many other functions, Smart Trolley ensures security measures by considering special cases and giving its solutions. These cases are mentioned below:

Omission: A customer forgets to keep a product into the trolley after scanning it.

Wrong Quantity (Short pick or Over pick): A customer scans one product but places multiple products in the trolley.

Condition Error: A customer attempts to take away products in the trolley without scanning them or A customer changes mind and removes the product from the trolley or A customer scans a cheaper product and places the expensive product having the same weight.

How Smart Trolley works to reduce Picking Error

(a) In Warehouse

In order to have an excellent warehouse performance, it is imperative to address human needs so that the errors can be minimized. Following table shows how smart trolley works in the warehouse to reduce various types of Picking Errors.

Miss Pick

In a case where a picker may have picked and scanned the wrong item is in addition to the correct item or instead of the correct item in the Smart Trolley, there is an important security measure to ensure the third level of check. It is the placement of a small camera with a barcode for image processing. So, when the product has scanned a picture of the product is taken at the same time the picker’s trolley ID and barcode picture is sent to the base station through sensor mote by ZigBee packets having relevant information.

Wrong Quantity (Short pick or Over pick)

The weight of products is an important factor to double check the identity of the product to protect against discrepancy or dishonest activity. A load cell, which is basically a weight sensor, is located at the bottom of the Smart Trolley. The output of the load cell helps in decision making against abnormal activities. For example, if the weight of the product measured by the load cell is not matching with the actual weight of the product then it is referred to as a case of discrepancy at the base station.

Omission and ConditionError

When we can create a shipment for order in any WMS, that you can easily export the associated picklist in the Smart Trolley Application. When the Picker will scan the product, this will automatically map with the list and also through scanning product picture will be taken to confirm the intended product from the Smart Trolley’s tablet.

(b) In Superstores and shopping Centers

Where superstores and shopping Centre operations are very much dependent on manual works and hence humans play critical roles and also Shoppers are human as well. To minimize the human factor error Smart Trolley can work in the following way for verities of error:

A customer forgets to keep a product into the trolley after scanning it or, A customer scans one product but places multiple products in the trolley or, A customer attempts to take away products in the trolley without scanning them

A customer changes mind and removes the product from the trolley

If any customer after purchasing the product changes his mind and wants to return the product, he just has to scan the product again, product picture will be taken to confirm intended product from the Smart Trolley’s tablet.

A customer scans a cheaper product and places the expensive product having the same weight

In a case where a customer may scan a cheaper product and places an expensive product in the Smart Trolley, there is another important security measure to ensure the third level of check. It is the placement of a small camera with a barcode for image processing. So, when the product has scanned a picture of the product is taken at the same time the customer’s trolley ID and barcode picture is sent to the base station through sensor mote by ZigBee packets having relevant information.

Conclusion:

For companies, it is necessary to design logistics processes in such a way that customer requirement is met. This applies to both manufacturing companies and logistics service providers. The order picking as a major logistics process has an important influence on customer satisfaction. In general, the impact of picking errors depends on the time of their detection. Errors that are detected during the picking by the order pickers themselves are not customer-relevant, but still, cause an expense in the form of time and costs for their correction. This expense increases significantly when the error is detected later in internal control, e.g. in an outgoing goods inspection. Troubleshooting, in this case, is more laborious because it could be necessary to re-stock a wrong item and to generate a new order to pick the right items. If defective consignments leave the warehouse and errors are discovered by the customer, this results in a complaint and the related costs of complaint handling in the short term. In the long term, this can also lead to the loss of image and customers. Especially when production systems are supplied just-in-time, costs for subsequent delivery via express or damages for a production line stop can explode. Undetected errors can have serious consequences. Assuming that a wrong component is installed in a vehicle or a facility, machines can be damaged or even human lives or health can be endangered. Use of Smart Trolley Application can reduce the consequences of Picking error in any logistics system.

References

Wheeler, C. (2014, June 30). Retrieved from NewCastleSystems : https://www.newcastlesys.com/blog/bid/349401/picking-error-problems-suggestions-and-solutions

Ali, S., & Riaz, M. (2015). Technology Evaluation and Commercialization_Report_SMART TROLLEY . Researchgate .

Bastian Solutions. (2018). Retrieved from Solutions: https://www.bastiansolutions.com/solutions/technology/goods-to-person

Dematic Global Website. (2018). Retrieved from Supplychain Solutions: http://www.dematic.com/en/supply-chain-solutions/by-supply-chain-function/case-picking/

DÖLLINGER , A., & LARSSON, T. (2016). Automated Storage and Retrieval within Contract Logistics . Gothenburg, Sweden : CHALMERS UNIVERSITY OF TECHNOLOGY .

Günthner, W. A. (2009). Active Prevention of Picking Errors by Employeeing Pick by vision.

Vanderlande. (2018). Retrieved from Warehousing: https://www.vanderlande.com/warehousing/innovative-systems/order-fulfilment/goods-to-man

Wikipedia. (2018). Retrieved from Automated storage and retrieval system: https://en.wikipedia.org/wiki/Automated_storage_and_retrieval_system