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Flexible enterprise solution in demand

Jun 01, 2021
Flexible enterprise solution in demand

Even in times of digitalization and artificial intelligence, ERP systems remain of central importance. Especially when technological advances are integrated in a meaningful way and the ERP becomes more and more an Industry 4.0 solution, it can even create completely new potentials. This makes it all the more important to learn about the current possibilities of these software solutions. The linchpin in these times is the degree of flexibility of a business solution. With the right enterprise solution, you are always flexible to adapt well to times like these at any time.


Transformation from ERP to Industry 4.0 solution

The goal of an ERP system is to map the company logic and use it to collect and process company-relevant information. In this way, management can be provided with a good basis for alternatives and optimal decisions and, in addition, the collected data can be used for optimal production control and planning. Opportunities for AI technologies that lead to many optimizations here currently lie primarily in the area of the Internet of Things (IoT) or, more precisely, the Industrial Internet of Things (IIoT). ERP systems support decision-making and process optimization by processing data.


The amount of data that could be available to a company through Big Data can be intelligently processed with AI. ERP systems are therefore an important component here. The enterprise solution then uses the results for optimal business management. AI technologies are becoming increasingly important because, for example, they use intelligent functionalities to determine current production sequences or enable proactive planning. In this way, a higher degree of automation and optimization can also be achieved through useful tools. However, the collection, analysis and processing of data naturally also leads to an enormous flood of data, for which sufficient capacities must be created.


Current development focuses are, for example, in the area of machine learning, neural networks and artificial intelligence. As a basis for the future use of algorithms - i.e. AI - special databases are being developed for ERP systems that allow extremely fast processes through in-memory computing. This makes it possible, for example, to implement predictive maintenance of plants: Past values are used to determine the current condition of the machine. Algorithms determine the next maintenance date so that unscheduled downtimes can be avoided.


Functional scope and flexibility decisive

Especially with the multitude of possible tools, it is becoming more and more important to know exactly where your own company currently stands and what it currently needs. And of course, in the dynamic and unpredictable times we find ourselves in, this can change at any time. This makes a high degree of flexibility extremely important. Markets and requirements are constantly changing. Agility and flexibility are required here. The chosen enterprise solution must therefore be able to be optimally adapted to one's own needs and at the same time be able to flexibly evolve at any time. Business solutions that offer an equally broad and deep range of functions, so that individual requirements can be optimally mapped, are advantageous here. In the best case, this also eliminates the need for external interfaces that can lead to information breaks. Good usability for user acceptance also plays a major role. And last but not least, the solution should be technologically up-to-date. This is essential for developments around Industry 4.0.


Since medium-sized companies in particular have many individual processes that should be mapped in the ERP system, the optimal enterprise solution should always provide the option of being able to adapt the system dynamically and flexibly to their own processes. A wide range of standard modules allows users to customize processes individually without having to develop everything again at the next release upgrade. This works with different software layers. There is a standard layer in which the developments are made. In another layer, users can carry out their own programming. Then the functions from the standard layer are copied here and released for the changes.


Flexible ERP systems can be used across all industries. Customers benefit here from providers with a wide range of industry experience. This is because some processes and work steps are similar, for example when steel coils are rolled up in the steel industry or fabric webs in the textile industry. Traceability and quality characteristics must also be guaranteed in almost every industry. In the case of industry solutions, a high degree of customer orientation in particular can lead to good solutions. ERP providers that offer customer-oriented functions usually work regularly on further developing the appropriate solutions. In the best case, this further development of functionalities takes place through good contact with the customer, seeing how an ERP system is used and adapted there. In this way, functions can be identified which, for example, can be adopted in certain industry solutions or generally in the standard. Open interfaces can also ensure that customers can quickly switch to newly developed functions.


The openness and flexibility of today's systems thus provide a convenient way to achieve the individualization that is just necessary. However, the demands are becoming more and more complex. Above all, individually designable ERP programs are attracting attention. Their flexibility does not hinder existing processes and they can rather grow with increasing requirements and integrate new demands. In addition, they make it possible to distinguish oneself from competitors through greater individuality.


One step further with IIoT

With the multitude of new developments, the question often arises as to how the enterprise system can meaningfully work together with IIoT solutions. For manufacturing companies in particular, IIoT devices are good ways to expand the flexibility of the enterprise. These can make a variety of data measurable from machines and systems on which they are integrated, and - properly evaluated - offer high potential. This applies, for example, to the optimization of decision-making and productivity.


Whereas in ERP data tends to be bundled for decision-making purposes, the orientation of IIoT is first more decentralized and autonomous, and the complexity of the overall system is distributed among a large number of individual components. However, IIoT is an important supplier of differentiated data for decision-making. The communication of all machines and products with each other offers high potential here and leads to a very high volume of data, which in turn opens up completely new business models and great opportunities. In order for business processes to benefit from this data and for new business models to be established, the ERP software must be accessible from any location, at any time, and from any end device. This enables the measurement of overall equipment effectiveness (OEE) and supports live production monitoring and detailed reporting. Another point is the IT infrastructure, which can process the decentralized data in the form of business processes in real time in a powerful way. At the same time, these IT infrastructures must be scalable as needed to respond flexibly to performance peaks or growth.


The integration of IIoT into production processes requires systematic implementation and integration: Sensors on the machine, supplemented by standardized data communication and a data platform for storing and evaluating the data, which is connected to a user-specific ERP system, can be regarded as the essential elements here. In this way, structures are created. Data can be recorded and is also made accessible for further processing. Thus, in the first step, machine data is to be captured and then made visualizable. In the second step, machine and system states are determined and documented in order to then recognize unplanned states in the third step, for example, which is partially supplemented by AI and enables the predictive maintenance mentioned above, for example.


Measures that initiate a development towards a smart factory and Industry 4.0 can lead to an extension of the service life and/or higher energy efficiency, increase the production volume as well as the product quality, serve to fulfill legal requirements and ensure functionality. This high increase in benefits justifies the initiation of measures towards an Industry 4.0 solution.


Introduction of an Industry 4.0 solution

When introducing a new Industry 4.0 solution with a comprehensive ERP system and suitable IoT tools, you should allow sufficient time and always carry it out in a highly structured manner. The system to be introduced should be intensively studied in advance and extensive test scenarios should be carried out before going live. A software introduction should always be seen as an opportunity to put processes to the test and try out something new. This does not mean adapting to the new software, but rather analyzing established processes together with the introduction, restructuring them if necessary, and above all optimizing one's own processes. In this way, the path to Industry 4.0 can become a real success story!


Article Courtesy: IAS India - Canias ERP Pvt Ltd

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