In the context of the Fourth Industrial Revolution this paper analyzes the factors that explain the degree of diffusion of some Information Technologies (ICTs) enabling Industries 4.0 in Chilean companies. In this group we find technologies such as: Big data, RIFD (Radio frequency identification), Cloud computing, ERP (Enterprise requirements planning), CRM (Customer relationship management), SCM (Supply chain management) and Computer security. Through the analysis of clusters, orderly logistic regression and decision tree, based on 2,081 companies reported in the Survey of Access and Use of Information Communication Technology (ICT) in Companies 2018 (MINECON, 2020). It is concluded that there is an important difference in technological adoption based on size from the volume of sales and the amount of direct labor. It is also noted that companies that subcontract and at the same time have ICT professionals are more likely to invest in this type of technology. We detected a “technological staggering” where companies begin by incorporating Cloud Computing and ERP and then increase in the number and complexity of the technologies used, achieving greater synergies and benefits in digital transformation. It is necessary to implement mechanisms for monitoring technical change to generate public policies aimed at leveling technological adoption in small and medium-sized enterprises. This work provides a global and intersectoral view of the process of diffusion of enabling technologies for Industry 4.0 through multivariate analysis techniques and data science, being a contribution to what is currently worked on focused on the study of business cases, on the monitoring of a specific technology or on an analysis of a specific productive sector.

Trabajó con nosotros desde el año 2000, primero participando como conferencista invitado en la Primera Conferencia Iberoamericana en Maderas y Productos Forestales y luego en distintos proyectos al alero del Dimad. Siempre accediendo a desplazarse a este lado del mundo, con generosidad para compartir sus conocimientos y experiencias.Fue un soporte importante de nuestro Magíster en Ciencias y Tecnología de la Madera y del proyecto Mecesup "Modernización de la formación de profesionales silvo-madereros mediante la acción integrada de las Universidades del Bío-Bío y de Concepción", en particular en la reforma curricular y modernización de la la actual carrera de pregrado, Ingeniería Civil en Industrias de la Madera.Thomas, colaboró estrechamente con los académicos del área de producción del Dimad, acogiendo a nuestros estudiantes en su grupo de investigación, cuando era profesor en la Universidad de British Columbia (UBC), Canadá, y recibiendo a profesores de la UBB en sus estudios doctorales y postdoctorales. Fue también un estrecho colaborador de nuestra revista Maderas-Ciencia y Tecnología, siendo miembro de su comité científico por 15 años.Personalmente, aprendí de Tom sobre el vínculo con la industria, de la investigación con sentido de desarrollo e impacto, y de cómo los estudiantes se integran a la investigación y a la transferencia. Pero sobre todo de lo importante de las relaciones humanas para lograr una buena colaboración y del uso del lenguaje para explicar lo complejo de manera sencilla. Tom era un "gringo", un gringo feliz que quiso mucho a Chile, su trabajo, su familia, sus amigos y su pasión, la pesca. En sus muchos viajes, hizo esfuerzos para conocernos y aprender español. Pensaba venir a tomar energías y descansar. Amante profundo de la naturaleza, de la conservación, creía y trabajaba por una industria forestal sustentable integrada a las comunidades locales, donde la tecnología fuera un medio para el progreso y no un fin. Fue preclaro en esos principios, antecedentes de la ahora economía circular y "green manufacturing".Siento no haber homenajeado públicamente a Tom. Pero la vida es así, "c'est la vie". Se fue antes de lo esperado. Esperaba verlo pronto y visitar su nuevo centro de transferencia en industria de la madera y construcción que había creado en Oregón. Años atrás había conocido su Center of Advanced Manufacturing of Wood, fundado por él en UBC y que nos inspiró en aquellos años a seguir ese camino en la UBB, acá en Chile.

Wood industry is key for sustainability and an important economic activity in many countries. In manufacturing plants, wood variability turns operation management more complex. In a competitive scenario, assets availability is critical to achieve higher productivity. In a new fourth industrial revolution, Industry 4.0, data engineering permits efficient decisions making. Phenomena difficult to model with conventional techniques are turned possible with algorithms based on artificial intelligence. Sensors and machine learning techniques allow intelligent analysis of data. However, algorithms are highly sensitive of the problem and his study to decide on which work is critical. For the manufacturing wood processes, Industry 4.0 is a great opportunity. Wood is a material of biological origin and generates variabilities over the manufacturing processes. For example, in the veneer drying, density and anatomical structure impact the product quality. Scanners have been developed to measure variables and outcomes, but decisions are made yet by humans. Today, robust sensors, computing capacity, communications and intelligent algorithms permit to manage wood variability. Real-time actions can be achieved by learning from data. This paper presents trends and opportunities provided by Industry 4.0 components. Sensors, decision support systems and intelligent algorithms use are reviewed. Some applications are presented.

In Latin América there are large exporting companies intensive in natural resources which do not connect with the SMEs in the territories. The aim of this study is to provide elements that explain the limits to the productivity of small and medium enterprises located in bio-based territories, providing inputs for a public policy that enhances local development. The case of sawmills located in the Province of Arauco, Bío-Bío Region, Chile, is studied. The results of a survey applied to 42 companies are analyzed, in the context of an initiative financed by the Regional Government of Biobío, which represent 84% of the total sawmills in the Province of Arauco. Different data science algorithms are used to generate clusters and decision trees. Based on the results, a heterogeneity within the group of companies is verified from the perception of the main problems, the processes that are internalized, the number of sectors it sells to and the cost of raw materials. Public policies recommendations are presented aimed at building support networks, improving quality standards through certifications, attracting, and retaining qualified human capital and promoting collaborative design among companies.