Hello everyone,
As many of you are aware, Industry 4.0 and smart manufacturing is widely gaining traction among many manufacturing practitioners.
One of the aims of smart manufacturing is to bring in more real-time intelligence to shop-floor and manufacturing planners, by employing different shop-floor data sources (For eg, smart products, advanced equipment, and machine sensors, collated through the Industrial Internet of things, RFID gateways, etc). The data collected from these shop-floor data sources can be processed by means of Artificial intelligence-based algorithms ( machine learning, evolutionary algorithms, etc) to produce optimized production schedules, process plans, service schedules, and maintenance plans. The application of such techniques has been researched by several researchers and numerous publications are already available.
However, at the same time, central to the functioning of any manufacturing industry are Enterprise resources planning packages, encompassing all the functions of a manufacturing business, ranging from procurement to production planning and control to service management and even auxiliary support functions such as accounting and packages.
As a result, there are two different software systems that can benefit manufacturing firms:
1. AI-based smart manufacturing tools which seem promising in improving production efficiency: Such packages are more manufacturing operation centric
2. Tried and tested ERP work packages, developed by numerous software firms: Such packages can focus on both the business planning and manufacturing operations management.
The questions that I often wonder about in this regard are :
- Have AI- algorithm-based smart manufacturing tools been integrated into existing ERP software?
- What is the level of maturity of ERP work packages with respect to AI-based intelligence algorithms ( particularly with respect to integration and hosting of AI-based work packages, API access to databases, software architecture)?
Many ERP work packages support multiple scheduling rules for a host of production scenarios such as flow manufacturing, make to stock, make to order, job shop- etc.
- But do they actually employ AI Solvers, such as genetic algorithms, search-based algorithms, Neural network models, reinforcement learning-based algorithms?
From my initial assessment of the market, I understand that we are staring at a situation where the development in these two work packages progressing is in two nonintersecting planes, with two separate software packages being the only way out- one for AI-enabled manufacturing execution and the other for ERP systems?
In that case, I'd be keen to know the market feedback-
- Are industrial engineers of today willing to accept the need for two separate software packages for manufacturing scheduling and control, considering that liaising with software systems is not their core job ?
I've found a few articles on Intelligent ERP systems, but they are pretty generic, and mainly focus on the need for ERP systems to integrate cloud and mobile-based support and automated inspections, but do not discuss much on AI solvers.
A search on google scholar does not reveal much either, with many articles proposing architecture for ERP of the future, integration with smart agents, etc, without discussing a lot on existing maturity levels and capabilities.
Looking forward to your valuable answers!
ERP systems, e.g. SAP, Sage, Oracle, IFS, and Dynamics, are well developed and adopted by enterprise companies. I trust Big data analytics and related technologies have been utilised for advanced planning. However, the cost and time for ERP implementation and integration is still a severe challenge to many companies. So, Google scholar may not show ERP capabilities and innovations that exist!
Dear Shohin Aheleroff, Some of the Cloud ERP providers are working on it, and they are closing the configuration gap that exists between PLM, CAD, ERP and CRM systems by using AI and machine learning.
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