Industry 4.0 What is Mobile Data Collection? - Definition and Benefits

Mobile data collection refers to the collection of order, goods and machine data. The integration of devices into the process flow has influence on efficiency.

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proLogistik GmbH

topsystem GmbH - LYDIA Voice Solutions

Zetes GmbH

PHOENIX Pharmahandel GmbH & Co. KG

Fraunhofer-Institut für Werkzeugmaschinen und Umformtechnik IWU

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KASTO Maschinenbau GmbH & Co. KG

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The mobile recording of order, goods and machine data at the point of origin not only increases flexibility in processing. The real-time recording also eliminates the need for a subsequent comparison of stocks. The efficiency of mobile data collection devices and the precise integration into the process flow have a considerable influence on the efficiency during use.

Modern components of information and communication technology are increasingly being integrated into production technology. This means that a large amount of different data with a direct or indirect reference to production is available for acquisition and processing. As a result, data as a resource is becoming increasingly important . But how can this data be captured, processed and made available as information that supports complex production scenarios?

“New and adapted methods and solutions for flexible acquisition, administration and problem-oriented evaluation are required in order to use the data profitably in the production and logistics environment,” says Dr. Tino Langer, head of the “Smart Factory - Digitization and Automation” department at the Fraunhofer Institute for Machine Tools and Forming Technology IWU in Chemnitz.

Flexible and error-free processes require powerful devices

The flawless and precise provision of products, for example, is essential in the pharmaceutical wholesale sector. At Phoenix Pharmahandel GmbH & Co KG, this is both flexible and precisely organised. The ERP systems transmit all necessary data to the scanning system. This carries out the picking tasks. The order picker scans the storage compartment and/or the respective product. Once this has been completed, the device displays the next picking task in a route-optimised manner. After all picks have been completed, he places the goods in the provided container. All necessary information is visible in the Business Intelligence System (BI system). In addition to this “basic” picking, there are a number of other specific picking orders that are carried out differently. For example, two-step order picking using transport carts or picking pallets.

“Support functions, such as checking the order container, stock queries, visibility of excess stock locations or replenishment tasks for manual and automated storage areas, complement the picking tasks. In addition, the system supports different inventory procedures. The conveyor technology provides a large number of orders in order containers in the outgoing goods department. This is where loading scanning is carried out on the respective vehicle,” says Stefan Pflug, Phoenix Management Germany, describing the complex process.

Using the device, the delivery drivers scan the shipping units against a loading list transferred to the scanner. It is not possible to swap or exchange missing or incorrect shipment units. At any time it can be seen how many and which consignment units still have to be loaded. At the pharmacy, a pharmacy-specific barcode is scanned and the shipping units to be delivered are displayed, scanned and acknowledged by the signature of the pharmacy staff.

New technologies enable greater transparency of data collection processes

In terms of mobile data acquisition and processing, much has changed in recent years with regard to technology at Phoenix. For example, legal changes in the presentation of prescription drugs have continuously replaced older scanners with 2D-capable devices. This has given greater importance to the transparency of processes, so that, for example, productivity and quality can be evaluated by area.

"The networking of the systems has progressed considerably so that the information from mobile data acquisition can also be used integratively in other systems. The use of BI systems and the associated higher transparency enable us to optimise processes sustainably. And scans along the entire supply chain show in real time where which goods are located," says Pflug, describing the company's developments."Mobile data collection creates a high degree of transparency in increasingly complex logistics networks and process chains. This is important in order to provide our employees with the best possible support in their daily tasks and to provide our customers with efficient, high-quality logistics services," he says, naming the benefits.

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The technology is currently used in all 20 German distribution centres of the Phoenix group, as well as in 15 other countries with a total of 120 locations. "This scanning system is the workhorse of wholesale order picking, with which we carry out up to 2 million transactions per hour on peak days", Pflug quantifies the volume. And he mentions further projects of the company:"The system still offers significant potential, in particular in networking with other functions, which is continuously being developed and rolled out in 15 countries".

"With ever more complex processes, employees must be enabled to make the right decisions through a clearly reduced wealth of information. As a result, in addition to the aspect of data evaluation for generating production-relevant information, the preparation and provision of information is gaining in importance," confirms Dr. Langer from Fraunhofer IWU.

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Dachzeile

Mobile Datenerfassungsgeräte bewähren sich in der Praxis

Dr. Tino Langer ist Abteilungsleiter Digitalisierung in der Produktion am Fraunhofer-Institut für Werkzeugmaschinen und Umformtechnik (IWU) in Chemnitz. Er beschäftigt sich mit verschiedenen Projekten zur mobilen Datenerfassung. Im Interview gibt er Auskunft darüber, worauf es beim Einsatz von MDE ankommt.

Dr. Tino Langer

Herr Dr. Langer, worauf kommt es beim Einsatz von mobilen Datenerfassungsgeräten an?

Die geforderte Leistungsfähigkeit des mobilen Gerätes ist wichtig, also die Frage, ob bereits eine lokale Verarbeitung möglich ist oder ob eine Weitergabe der Daten, beispielsweise an eine Cloud, zur Weiterverarbeitung erforderlich ist. Auch die Größe des Displays ist wichtig, denn sie beeinflusst die Art und den Umfang der darstellbaren Informationen sehr stark. Und natürlich spielt die Konnektivität der Geräte eine Rolle, um sicherzustellen, dass diese mit anderen IT-Infrastrukturen wie WLAN oder Bluetooth kommunizieren können.

Was sind die Herausforderungen beim Einsatz von mobilen Datenerfassungsgeräten?

Grundsätzlich birgt eine vereinfachte Datenerfassung auch die Gefahr, Datenfriedhöfe zu erzeugen. Die Fragen sind daher: Was tun mit den Daten? Wie daraus Informationen und Wissen generieren und wie zu Wertschöpfung kommen? Welche Analyseansätze wählt man also, um von Big Data zu Smart Data zu kommen? Eine gezielte Datenanalyse sollte vor diesem Hintergrund also immer in Zusammenarbeit von Informatiker und Maschinenbauer beziehungsweise Logistiker, der den Prozess und die Maschine kennt, erfolgen. Eine weitere Herausforderung bedeuten die fehlenden Standards mit Blick auf die Schnittstellen der Datenlieferanten: SPS, produktionsrelevante IT-Systeme und andere. Und natürlich ist die Schaffung intuitiver Lösungen zur Mensch-Maschine-Interaktion und die Verknüpfung von Daten aus unterschiedlichen Systemen zur Ableitung neuer, bisher unbekannter Zusammenhänge eine Herausforderung.

Was wird in naher Zukunft mit MDE technisch möglich sein?

In Zukunft wird durch geeignete, fortschrittliche Lösungen der Mensch-Maschine-Interaktion der Mitarbeiter leichter und gezielt mit den Informationen versorgt, die er zur Bewältigung der meist komplexen Produktionsumgebungen benötigt. Die Informationen werden dann kontextbasiert mobil zur Verfügung gestellt, das heißt: in Abhängigkeit von der Rolle, der Aufgabe und dem Ort des Mitarbeiters. Zudem wird die ‚normale‘ Wahrnehmung durch Augmented-Reality-Technologien angereichert, um so Zusatzinformationen ohne ungewollte Beeinflussungen bereitstellen zu können.

Was hat sich in der Datenerfassung und -verarbeitung mit Blick auf die Technik in den letzten Jahren geändert?

Wissenschaftler und Unternehmen arbeiten daran, Kommunikationsstandards zu etablieren. Während früher eine zentrale Datenerfassung üblich war, geht der Trend heute zur Dezentralisierung. Leistungsschwache Low-cost-Lösungen nah an der Maschine weichen Daten-Gateways und IoT-Gateways. Wichtig sind in diesem Zusammenhang die leichtere Zugänglichkeit von Sensordaten und eine allgemein deutlich höhere Durchdringung der Produktionstechnik mit Sensoren und IKT, als noch vor einigen Jahren.

Vielen Dank für das Gespräch.

Material flow and machine condition always in sight with networked machines

The manufacturer of Kasto metal saw and storage technology uses smartphones with an integrated barcode reader, telephone, camera and various interfaces for mobile data collection. In addition industrial tablets with appropriate equipment. The data is captured by barcodes/RFID, voice and manual input and transmitted to the warehouse management or merchandise management system.

The company has now launched an app for the clear handling of its sawing machines. This allows users to query and monitor the status of their sawing machines via smartphone or tablet at any time and from anywhere on the company premises and to react quickly if necessary. The app provides a status overview of all Kasto sawing machines in the network. It provides information on the status of the machines, for example, whether they are running in automatic or manual mode, whether there is a fault or whether the machine is in tool change status. If a saw is running in automatic mode, the app can access the information stored in the respective machine controller. This provides the user with precise information on all relevant parameters such as article, cut-off length, target and an actual number of pieces as well as feed and cutting speed. If an error occurs during operation, the app visualises the pending error message and the user can react quickly. Downtimes can be reduced to a minimum.

"The use of devices has made faster data acquisition and processing possible, which contributes to a flexible working method. Thanks to global data access, the required data is available at a glance everywhere," says Sönke Krebber, member of the management board.

For the device, there are already some very precise and efficient applications. Currently, however, captured data is often only analysed and processed according to its original reason for capture. "A decisively increased added value can be achieved if already captured and processed data can be further processed beyond their original reason for entry," says Dr. Tino Langer, giving an overview of future applications.

* Annedore Bose-Munde is a specialist editor for economics and technology

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