Building a Factory Knowledge Base: Digitalization and Integration of Manufacturing Information

Introduction

The technologies provided by the Industry 4.0 paradigm help to improve business organization and automate industrial processes by adding the concept of interconnection between devices and information systems to the existing technologies. Among the most important advantages of interconnection there are the creation of 'intelligent' production thanks to data collected and analyzed in real time by machining centers, machine tools and devices and the production of a large amount of data (Big Data) that can be processed to plan new strategies. In this context the production mostly focuses on the personal needs of the consumer: companies innovate and introduce new products on the market led by the consumers, trying to anticipate their needs. Thus, lean development approaches are needed to quickly test the products and reduce the time to market. The past decades have been characterized by this trend, known as the concept of mass customization. This concept reaches its extreme with the One-of-a-Kind Production (OKP): every single product is different for each customer. With the new technologies of the Fourth industrial revolution, meeting the demands of customers and innovating continuously are not only possible, but they are an essential requirement for any company, in particular small and medium sized, that wants to compete in the market (Muffatto 2000, Wortmann 1997, Tu 1997, Dean 2009).

An increasing number of industrial operators and manufacturers are adding industrial connectivity to their assets. The Internet of Things (IoT), a now fundamental concept of the Information Technologies (IT), provides for machines, operators and all the resources are able to interact among each other sharing data about their status and all the issues that happen during the production. The ability to store, integrate and use these data is an important feature to accomplish for a company of the fourth industrial revolution. This feature can be seen from three different points of view: horizontal integration, vertical integration, and end-to-end integration (Vaidya 2018). Horizontal integration refers to data along various business functions like for example production, design, R&D, purchasing, human resource or accounting and finance. Vertical integration requires the involvement of players and partners who interact with the company. Integrating the systems of various companies along the value chain is essential to allow a coordinated and efficient work. Finally, the end-to-end integration operates throughout the life cycle of the product and makes it possible to achieve excellent results that go further the production line and the supply chan.

To achieve system integration, it is necessary that IT platforms implemented in a company cover the process of product design, to allow innovation towards customer needs, and the production activity itself, to minimize costs and lead times. The goal of PLM systems is to allow the interaction and coordination among people (not only designers), thus enabling the knowledge exchange, transfer and reuse. The purpose of a MES is to control and manage the production in detail, providing real-time information of the whole process, right through to the completion of the order. MES, creating knowledge from the activity of machines, operators and sensors, creates a digital twin of the system through which it is possible to control the progression of tasks and compare it with the production planning.

Through the integration between PLM and MES, designers could observe what is happening in production, receive feedback and check where anomalies have occurred to ensure that these errors or complications do not occur again in the future. If made easy to use, his knowledge could be of great importance during the design of a new product, especially in the case of OKP, where it is usual to design a new product for each customer, customizing the characteristics according to its needs.

These companies need several trial-and-errors cycles before find the final one to design a new process for the new product. Actually, in the most of these companies, the knowledge of the trial-and-errors cycles remains in the minds of the people, or, at best, transferred verbally, and then, over time, inevitably lost (Bruno 2014, Bruno 2018). Similarly, it is also difficult for a production manager to find information related to the checks to perform before and after the execution of an operation on a machine, and for an operator to report in a structured way the occurrence of problems and anomalies during the production. Oral communication and knowledge based on the experience of the operators do not allow companies to compete in the global market and therefore this implies the need for a knowledge-based information system (KBS) that can contain and make this design knowledge easy to consult.