Cyber Physical System with Manufacturing IoT

IoT

Cyber-Physical Production System GD.findi/CPS

Knowledge-intensive Monodzukuri in Monodzukuri IoT era (knowledge centric)
Although the IoT era has been opened, we are now faced with the task of the introduction of cyber physical production in the manufacturing industry.
Based on the concept of "Simulation Integrated Manufacturing (SIM)", LEXER RESEARCH Inc. provides the Cyber-physical Production System (CPS) in the IoT era.

The introduction of "Simulation Integrated Manufacturing" ➡  SIMバナー

To be specific, our CPS concept represents that with the introduction of IoT at shop floor, it monitors the status of the entire production plant or the entire supply-chain in real time, and besides it generates a plan that enables to optimally operate the entire production activity according to the purpose of business. Ultimately, this system aims to send precise instructions to the work site in a timely manner by utilizing IoT.
By virtualizing shop floor as a physical space and synchronizing it with cyber space utilizing IoT, it transfers the activities of mechanical system and human system to the same management space that has been difficult to manage integrated because it has been a heterogeneous activity in the past. By bringing them to the homogenous space, it enables to handle these activities integrally. For example, now it is able to respond the optimization plans which has been in difficulties at the shop floor until now.

全体最適

GD.findi/Tasks of production sites solved by GD.findi

It is assumed that there is no necessity to explain the manufacturing site for those who already knows about it well. However, I would like to point out that today there are many issues in manufacturing site. In particular, one has to respond to the demand of the market in order to cope with the small-quantity batch production. It is a matter of difficult task to make a short and thorough production plan without with less waste. In addition to the need for changeovers, the emergency response to express goods and the so-called brief stop in production line would be affected, consequently the production plan will be also delayed. As a result, the productivity of production line and factory will decline and it tends to be high cost production. Besides, as side effects, the in-process inventory between processes will also increase.
GD.findi/CPS optimizes the production plan by cyber physicalization (the conversion of IoT) of such production form. We constantly optimize the production schedule for express goods on each occasion, and we will continue to doing our best to the utmost in response to various changes and production demands occurring in the production line. As a result, it is possible to respond to fluctuation factors that conventional production managers could not respond adequately in real time and best practice, and be able to operate the production site smoothly.

GD.findi / CPSの導入

Production AI with massively parallel simulation

The following figure shows the configuration of GD.findi/CPS. GD.findi/CPS consists of three system.

First one is the IoT part that makes the production line as cyber-physically.
Second one is the part of production management dealing with the production plan and work progress.
Third one is the part of AI system by the massively parallel simulation which optimizes the production plan.

The biggest feature here is the production AI system that optimizes the production plan in real time by massively parallel simulation.

Conventionally, we have tried to respond to the planning of production plan with the technology a socalled "scheduler," however it is getting more difficult to deal with complicated demands for today's production. The reason for this would be as follows: the way of flowing (routing) is becoming complicated along with the composition of production line, the demand for production such as the multi-product small-volume production becomes strict, and accordingly, it is necessary to respond dynamically it depending on the conditions such as changing the setup and having multiple steps of the worker. It is also because that it has become difficult to respond the requirements of the site under the "standard logic to search purpose solution" led by the conventional schedulers. Therefore, GD.findi/CPS has realized an entirely new way of answers using the production simulator technology of LEXER in any ways and thoroughly in response to this problem.

In this case, rather than executing the logic of searching the objective solution, a large number of computers with production simulators are placed on the server system, a number of possible conditions are evaluated in a massively parallel manner, and finally we will obtain the desired solution by selecting the nearest condition towards the goal.

The merit of this method is that it is possible to deal with complicated production issues of today because it can sufficiently describe the flow of complicated processes such as routing and set-up change, and multi-step process in the manufacturing simulator.
Furthermore, not only the deterministic solution, it is such a great advantage to suggest candidates of various real solutions that can be adopted at the site. Surely, it is needed to have a big calculation power to execute the production simulation of enormous cases. However, since GD.findi's simulation engine, GD.findi/Reactor has extremely high process ability, it is proven in various cases that the system can provide sufficient performance for requirements of today.

The Structure of Cyber Physical System (CPS)


Flow of Production Optimization Processing by GD.findi/CPS

This is the work flow in floor shop.
The work progress from top that means sales side to shop floor.
But there are many trouble and shop floor does not achieve its duty.
Regarding this problem, when the progress is delayed for production schedule, shop floor will get a current situation from IoT system and send it to simulation system for optimization in cloud. On the other hand, simulation system has a lot of parallel simulation engines on cloud and generates optimized production schedule.
By using optimized schedule, sustainable production will be carried in shop floor.


Dynamic Optimization by Massively Parallel Simulation

Control panel of GD.findi Predictive Mining

Example of Control Screen of Dynamic Optimization System

Case Study: Draft of work plan and Direct by smart device

Case Study: Work instruction at the production site

Case Study: Work Instruction and actual input using by smartp hone

Support Cyber-physical Production System "GD.findi CPS Suites for Manufacturing IoT"

It is able to build cyber physical production system by using WEB service or development tool kit provided by LEXER.

全体最適

Products / Services


Informationimage

The 4th Monozukuri Nippon(japan) Grand Award and Minister of Economy. Trade and Industry Award

The 4th Monozukuri Nippon(japan) Grand Award and Minister of Economy. Trade and Industry Award

Concept & Technology
Innovation from LEXER

Concept & Technology Innovation from LEXER

Tech Magazine
Practice of GD.findi

gdfindi_katsuyou
PAGETOP