Not all enterprises are technologically sound! They often face difficulties in deciding which technologies they should invest in and which they should avoid because they will hardly do any good for them. On the other hand, they have to grow up–their sole aim and a responsibility too.
Today, the best form of technologies available for enterprises is Enterprise Resource Planning (ERP). The ERP system is a modular software system integrated into the core / functional enterprise operations of an organization.
When it comes to the ERP implementation, there are different approaches followed, such as on-premises, cloud, and hybrid, which is a mix of two like, Platform as a Service (PaaS) and Infrastructure as a Service (IaaS). Historically, ERP has been bulky software systems associated with huge investment and end-to-end implementation, but now, with the global emergence and growing acceptance of cloud, things are turning out to as easier and affordable as SMBs can also take the advantages of in greater numbers.
ERP exists in the market for nearly four decades. In 1990, the abbreviation, ERP was first used by Gartner Group to extend upon the capabilities of material requirements planning, and later manufacturing resource planning apart from computer-integrated manufacturing.
Now developers around the world are experimenting with ERP systems by including next-generation capabilities based on AI, ML, IoT, and Cloud. These future technologies are making ERP software development smarter. Here is how ERP software development turning up smarter with the combination of AI, ML, IoT, and Cloud
1. ERP to turn up as a self-learning knowledge system
An ERP turns smarter when it has the self-learning knowledge provided by AI, ML, and Cloud. This sort of system can organize a business, from shop floor to top floor. The self learning capabilities added to ERP with the cloud featuring integrated key ERP web services, apps, the real time-monitoring accelerates the entire system’s quick learning. The system also includes several APIs and web services that empower a business connecting with many suppliers/buyers at the same time.
2. ERP systems with AI-ML and voice-commanded enabled virtual assents
Virtual agents are now showing up their potentials in redefining many areas in different manufacturing operations. Market’s top virtual assistants, Amazon, Alexa, Google Voice, and Cortana come with the capability of being modified according to operation-related requirements of a business. Some business engaged in manufacturing have also informed about piloting voice-agents having integrated ERP that helps them provide detailed instructions to shape Configure To Order (CTO) and Engineer To Order (ETO) productions.
3. IoT data for AI-ML enabled cloud ERP
The integration of IoT into an ERP helps at the data-structure level to realize speedy wins. IoT devices generate massive data streams that can be capitalized by an ERP based on the cloud. When an ERP, with the integration of AI and ML technologies, use IoT data, the system turns out to be capable of bridging intelligence gaps, which many businesses face in pursuing new business models.
4. Getting insights into OEE via AI and ML capabilities
With AI and ML, the ERP can provide insights into how Overall Equipment Effectiveness (OEE) can be bettered. This functionality just doesn’t present in the ERP of many organizations; however, they eagerly seek for it to stabilize and then normalize performances on shop floors. With the capabilities of AI-ML, IoT, and cloud, ERP serves as an always-learning knowledge system that quickly monitors data in the real-time, and creates required insights for improvements.
5. ML capabilities help in tracking product-lots and predict their quality standards
With ML, an ERP system gets tracking /tracing capabilities which can help a business predict which product-lot may carry higher chances of failing for quality checks.Past patterns and data set help in designing this capability.
6. Using AI and ML to close gaps between PLM, CAD, ERP and CRM systems
Apart from ERP, businesses also use other systems like CAD, PLM, and CRM. Businesses use these systems with huge gaps existing between them to attain a single goal. The gap can be closed by a cloud based ERP in almost all given cases. Cloud ERP can alleviate a number of conflicts such as how the engineering department in a company designs a product using CAD and PLM, how sales & and marketing department sells the same product with support of CRM and, how manufacturing department builds it.
7. Using ML to decrease equipment breakdowns and increasing asset utilization
With ML capability, ERP helps enterprises keep tabs on equipment and machineries, and timely launch maintenance operations to avoid sudden breakdowns. The system can analyze machine-level data and determine when a particular part of a machine requires a service or replacement. This helps the business keepings its business health up to date.
8. Implementing self-learning algorithm to predict product-related problems
Legacy ERPs cannot be added with enough functions to predict any sort of problems but an ERP with advanced technology can do this. A cloud-based ERP with AI and ML capabilities can compare present incidents with past data and generate reports that can be used to predict product related problems to arise in the future.
9. Using machine learning algorithms to enhance product quality
An ERP can capture the quality-data from suppliers to customers once the system is scaled across the entire product-lifecycle with cloud implementation. The data can help in generating actual reports on why products fail.
10. Getting precisepredictions for demand and facilitate better collaborations
Business gets higher prediction accuracy when implements a cloud ERP. Developers achieve it via the high quality data used by a self learning system, which itself is based on AI and ML technologies. Business is able to fine-tine itself at several places when the data is used to improve activities of sales, marketing, and promotions programs.