## 1 Introduction  
This paper describes the design and implementation of an industrial safety system based on the Alexa voice assistant for a three-phase motor's ignition and rotation change. The interest in voice assistants has been increasing due to their functionality, scope of applications, and ease use. Ref. [1] proposed to control a computer with a voice assistant, based in Python. This work is oriented towards improving the computer-human interaction, but not in an industrial environment. Studies and research have been conducted on applying voice assistants in the industrial area [2]. Talking about Industry 4.0 and its technologies allows thinking about a new form of interaction between humans and machines within an industrial environment, as is the case of intelligent voice assistants, where user voice commands can be recognized, understood, and processed to give a response based on a request [3, 4], allowing us to achieve a more collaborative and familiar environment, since more natural communication typical of human beings will allow more efficient and understandable interactions. In this way, ref. [5] researched the needs, requirements, and expectations of the use of voice assistants in industrial equipment maintenance for future technological implementation. In industry, the development of these applications is increasing the trend to eliminate screens and keyboards, allowing the operator to have both hands free to engage in other activities while giving orders to the production system [4; 6]. In [2], the authors propose an industrial voice assistant based in Raspberry Pi3 integrated into an industrial modular architecture system to compare results achieved from the actual process with a virtual digital twin of the system. Still, in this case, the proposed solution only works in a noise-free environment. Others applications of assistants have been found, such as the implementation of a voice assistant, based in Google, with the help of the IoT to replicate an industrial process in which two variables must be controlled in real time, temperature and humidity, and this is achieved with the help of an ESP8266 microcontroller, which powers up and holds the actuator, which is not mentioned in the work [7]. The Alexa voice assistant was connected to a LOGO PLC through a Raspberry PI that controlled a frequency variator to control the speed of an industrial AC motor [8]. In [9], the industry does not use voice assistants as operator helpers. The author uses Alexa and Raspberry Pi to interact with a PLC to determine the status of its inputs and outputs and production reports. All the aforementioned works use Raspberry Pi as an interface between the voice assistant and the industrial equipment. Still, the operating system and the industrial equipment may also crash. In addition, the Alexa voice assistant for interaction with an industrial robotic arm using a cloud database DynamoDB through client/server communication was mentioned in [10]. The system is fully proprietary and not open to improvement. In industrial maintenance, ref. [11] has created a voice assistant with augmented reality to provide assistance and guidance to operators to care for the end effector of a robot through a database without interaction, while ref. [12] worked on prototyping a voice assistant to maintain a milling machine using a mobile device. Research in quality control [3] developed an intelligent assistant for the essential process of quality control of parts with colors applied by a robotic arm through the integration of three technologies: voice assistant, artificial vision, and Internet of Things. It should be noted that within all the studies, it has been commonly found that the limitations of the application of voice assistants in industry are a product of factors that directly affect the process of voice command recognition and processing [1]. Among them are speed of speech, technical language learning, ambient noise, externalization of plant data, and variation in accents.