Alessandro Massaro - Electronics in Advanced Research Industries

The Plan concerning the occurring variations.

The actions to Do and to be controlled.

The Check of the executions by validating expected results.

The Act involving all the activities about the process, the standardization and stability, and improving the existing procedure.

The XmR chart, through the upper and lower control limits, provides the limits of an industrial production process mapping at the same time production results. As a further diagram to adopt for process mapping, a fishbone diagram (Ishikawa diagram) is a cause‐and‐effect approach able to track imperfections, variations, defects, or failures. This diagram is structured as a fish's skeleton with the problem at its head and the causes for the problem following the fish bones. In order to also predict defects or production failures, big data systems facilitate the analysis of the historical data. Big data systems implement NoSQL technology based on the following main categories:

key‐value distributed

document oriented

column oriented

graph oriented

However, some NoSQL DBMSs may have features that belong to more than one of these categories. Some common big data systems are Cassandra, MongoDB, and Hbase.

The interoperability of technologies is a fundamental element for the upgrade of the information system and in general for the production. Figure 1.8shows the interoperability of different technologies involved in Industry 4.0 and Industry 5.0 environments. The diagram includes all the main technologies for control and actuation supporting production auto‐adaption managed by the AI engine.

Figure 1.8 Interoperability of different technologies involved in Industry 4.0 and Industry 5.0 environments.

The technologies of Figure 1.8are interconnected in information by exchanging data with different software tools. The components of an innovative information system are divided into two main categories:

Transactional applications: systems and procedures supporting IT and enterprise resource planning (ERP) systems.

Decision support system (DSS): systems and procedures supporting strategic decisions and production processes management by data mining.

The ERP systems are developed for finance, logistics and in general for supply chain management. Subsequently ERP systems evolved into material requirements planning (MRP) tools implementing Business Process Re‐engineering (BPR) logics. The peculiarities of ERP systems are:

integrated solutions

functional modules

information centralization

real‐time availability

fixed functional schemes (standard models)

customer customizations

financial compliance

The implementation phases of ERP systems are summarized by the following steps:

Software selection.

formulation of the business process modeling (BPM).

mapping of existing processes (“AS IS” mapping).

definition of a new implementation scenario concerning future production processes (“TO BE” mapping).

BPR process redesign.

Production gap analysis (detailed list of missing production features).

Formalization of formal documents for the validation of new processes.

System parameterization.

Prototype creation.

Testing of the whole information systems.

The main ERP functions are:

management control

management of purchases and receptions

sales and distribution management

warehouse and logistics management

project management

production, orders, and account processing

human resources management

The upgrade of the ERP systems involves AI implementations, thus improving DSS dashboards and decision‐making processes of the whole supply chain. ERP and other software tools must be interconnected in information infrastructure enabling real‐time data processing, sensing, and actuation. According to the architecture of Figure 1.9, information systems interconnect different enabling technologies by means the use of the bus or of the ESB. DBs are synchronized and managed by an advanced ERP having different functions including data migration into the big data system. All the other facilities such as IoT, PLC sensing and actuation, AR and process simulation, are implemented through human–machine interfaces (HMIs) interconnecting the tools with the information system. The information systems are typically managed by a bus or a ESB line.

Figure 1.9 Information system interconnecting enabling technologies.

The bus system is a set of internal connections for the transmission and exchange of signals, supply voltage, and ground potentials. The exchange of signals between the microprocessor and the input and output interfaces therefore takes place via the bus system. The bus lines are classified as:

Address bus: allowing the access of the addresses of the individual boards.

Data bus: reading data from the input cards or data transferred to the board outputs.

Command bus: managing command and control signals within the controller.

Concerning technological limits, the challenge is to improve performance for an innovative Industry 5.0 scenario based on full production automatisms. Table 1.7lists some possible technological limits characterizing innovative technologies to integrate in the company information system.

Table 1.7 Possible limits of advanced technologies and technical risks.

AI, artificial intelligence; AR, augmented reality; GPU, graphics processing unit; IR, infrared; IRT, infrared thermography; PLC, programmable logic controller.