BioTech 4.0

A joint venture of LaMACS/DEQM and LAC/D.I. of PUC-Rio

Biotechnology

In almost all sectors of industry, Biotechnology and Bioinformatics have recently gained a huge momentum as they became the essential ingredients for an environmental friendly and sustainable economy. For example, Biotech industry is accountable for renewable fuels for vehicles, for huge advances in biologic/natural medicine, production of lignocellulosic biomass, extraction of ores from biocomposites, and bio-plastics.

However, compared to chemical reactions production processes, Biotechnology production processes are much more difficult to control due to the need to maintain the precise conditions for the adequate  growth of the (living) culture medium, even under very subtle changes of the environment conditions, such as temperature, pH, moisture, pressure, oxygen, biomass, etc, as well as other microorganisms in the ambient.

Along this line, it is well known that Biotech production lines can much benefit from Bioinformatics, Data Analytics, the accurate, timely and continuous monitoring and the partial or full automated control of the production process. Thus, Biotech 4.0 aims at the adoption of  Industry 4.0 methods and technology (including the Internet of Things, Cloud Computing and Data Analytics), in the biotech industry so as to enhance the productivity, the security and the logistics of these production processes. This is especially necessary in Brazil, where the biotech industry is growing on the basis of several new discoveries about raw material and viable production processes and products, but is still lagging behind in terms of a digitalized production technology and automation

The Industrial Internet of Things

Worldwide, the use of industry equipment, machines and smart devices with smart tags, with sensing, local processing and Internet-wide communication capacity is growing and is a central to element of  Industry 4.0, and henceforth also of BioTech 4.0. In this context the Industrial Internet of Things (IIoT) connects these smart machines/equipment to the Internet and promotes communication between individuals and machines, and also directly between machines (M2M), facilitating decision making and enabling automation of the production, fine-tuned control, better logistics, early detection and prevention of equipment malfunction, etc.

However, despite the potential operational, analytical and quality control & insurance benefits of Industry 4.0 this initiative is yet in its infancy – especially in Brazil [Biominas, 2011]. Therefore, there is much need for studies and automation experiments with instrumented prototypes that simulate real processes of the chemical and biotechnology industry at laboratory scale, so as to identify the specific automation problems and demonstrate the concrete benefits of the continuous monitoring, automated control and data analytics for the biotech production process.

Goals of the Project

By deploying, integrating and instrumenting (with sensors and actuators, for monitoring and fully automating) a Lab-scale Pilot Production Line (PPL) with emulated, yet highly representative and typical phases of the biodegradable polymer production process, this project has two main goals:

Initial Prototype

The initial prototype of the PPL will perform, as first step, the fermentation of the hydrolyzed sugarcane bagasse for production of L-lactic acid by the Lactobacillus sp. Due to its versatile applications as an acidulant, flavour enhancer and preservative, lactic acid has occupied a prime position in food, pharmaceutical, cosmetic and other chemical industries. Recently, use of lactic acid has expanded to be used as monomer in polymerization to form polylactic acid (PLA), a polymer of great interest because of its biodegradable properties.

hence, in a second step, the PPL will emulate the use of L-lactic acid to produce lactic Polyacid (i.e. biodegradable polymer) [Gupta, 2007].

Figure 1: Typical recycle process for production of lactic acid

Academic Partners

BioTech 4.0 is a multidisciplinary project that gathers experts from the Biotechnology/Chemistry Engineering and the Computer Science departments of PUC-Rio, and will be executed through the LaMACS and the LAC labs. While the former group is specialized in biotechnology and chemical industrial processes and the latter has more than seven years of experience with Internet of Things, their cooperation is just the perfect match of scientific/technical skills to reach the goals of this project.

The Laboratório de Modelagem, Automação, Controle e Separação (LaMACS) will be responsible for assembling, maintaining and extending the PPL. Research in LaMACS is focused on biochemical and biotechnological processes with emphasis on modeling and simulation of chemical processes, industrial automation, process control (simulation and experimental), modeling with artificial intelligence (use of neural networks, fuzzy logic and neuro-fuzzy) and controllers with artificial intelligence, experiment planning and optimizations, failure detection in production processes, polymer processes, biomass delignification and biotechnological processes (scale up and operation with bioreactors). The lab also uses computational tools, such as MATLAB and Simulink, Scilab and VBA, as well as the AspenTech process simulator (HYSYS and Aspen Plus, Polymer and Dynamics).

The Laboratory for Advanced Collaboration (LAC), associated with the Department of Informatics of PUC-Rio and coordinated by Prof. Markus Endler, will be responsible for the development, deployment and customization of the software infrastructure (middleware) for the monitoring and automatization of the production process.
This middleware, named ContextNet will be responsible for providing reliable (wireless) communication with low latency, mechanisms for collecting, aggregating and filtering the data obtained from sensors and controlling the actuators present in the automation of the industrial process being replicated.

Basis Internet of Things Technology
In a nutshell, the ContextNet middleware [Endler 2018] consists of:

In both the cloud and the Android device, ContextNet further allows for the use of a powerful real-time data flow analysis technology called Complex Event Processing (CEP).

CEP consists of a stream processing engine capable of  detecting quite complex patterns of events occurring in the data flow. By loading rules described in an Event Processing Language (EPL), a SQL-like language with pattern and window specifications, it is possible to monitor the flow of sensor data arriving in the system and to instantly identify the occurrence of temporal, logical and / or causal patterns of events received within time or event windows. CEP has been widely used in industry, logistics, transportation, energy plant monitoring, etc. ContextNet has the advantage of brining means for a flexible and distributed  deployment of CEP both in the cloud as well as at the IoT edges, close to the BSA objects.

In the scope of BioTech 4.0 the BSA are the different kinds of sensors and actuators integrated with, or attached to, the equipment that will communicate through wireless links (WiFi, BLE or other low-Power radios).

Call for Industry Partnership and Sponsorship

Industry partnerships and sponsorships for this project are very welcome. We are particularly interested in partnerships that want to test and further employ IoT technology and data analytics methods to innovative and environmental, economical and/or socially relevant biotechnology production or control processes, and which are willing to support the BioTech 4.0 by lending or donating new equipment and technology, or otherwise issuing consultancy or development contracts with the team.

Contact

For more information, please contact the two principal investigators: Prof. Brunno Ferreira dos Santos (LaMACS) and Prof. Markus Endler (LAC) through their Email addresses: bsantos@puc-rio.br, and endler@inf.puc-rio.br