i4Plas: Applying Technology to the Challenges of Plastics Manufacturing

At ColombiaPlast 2026, we presented i4Plas, the Centre for Digital Transformation in the Plastics Industry. This joint initiative by Acoplásticos, the Colombian Plastics and Rubber Training and Research Institute (ICIPC) and KERN IoP was established to help plastics processors explore, test and apply new technologies to real production problems.

Why we created i4Plas

Working alongside plastics-processing plants, we regularly encounter the same challenge. Sensors, software, artificial intelligence, machine vision, robotics and analytics are advancing rapidly. Yet companies still need to determine which technologies deserve evaluation, which production problems they can address and how to demonstrate their usefulness on the plant floor.

That is where i4Plas comes in. A manufacturer may be dealing with scrap, downtime, energy consumption, traceability, process instability or insufficient information about a machine. The first step is to define the problem, establish the data required and agree how outcomes will be measured. Only then can the relevant technology be selected and tested.

Start with the production problem

The initial i4Plas roadmap focuses on challenges that frequently arise in plastics processing. Different problems call for different tools and levels of technical complexity.

• Scrap and quality variability. Process-data acquisition, online statistical process control (SPC), machine vision, analytics and models that relate manufacturing conditions to product quality.
• Unplanned downtime. Sensors, condition monitoring, machine-state records and data analysis to identify the causes of lost equipment availability.
• Energy consumption. Electrical measurements and analysis by machine, auxiliary equipment, operating state or cycle, together with indicators that allow comparable production conditions to be evaluated.
• Circular economy and traceability. Identification of materials and products, digital product passports, data traceability and technologies that support material sorting and recovery.

In some cases, a reliable measurement and a well-defined indicator provide everything needed for the next step. Other applications may justify machine vision, predictive models, digital twins or artificial intelligence. The choice should follow the problem and the available evidence rather than the novelty of a technology.

How we intend to work

A technology demonstration can introduce a tool, but its value is best tested in an actual manufacturing process. That is why i4Plas envisages assessments, experimentation, pilot projects and training. A project might start with one machine, a single manufacturing cell, one product reference or a specific variable. A plant-wide digitalisation programme is not a prerequisite.

A pilot must answer a specific engineering question and produce a useful comparison. For an energy study, this means deciding what to measure, under which production conditions and with which indicator the results will be compared. For a scrap problem, process measurements need to be related to quality information. The method depends on the question.

This is particularly important in plastics processing. A single data point rarely explains what is happening. Analysing productivity, energy or quality requires context: machine, mould, material, product reference, auxiliary equipment, processing parameters, cycle, operating state and production outcome.

Technical collaboration to strengthen the sector

i4Plas brings together complementary capabilities. Acoplásticos maintains close ties with manufacturers and the sector’s challenges; ICIPC contributes expertise in materials, processing, research, training and technology development; and PM Tec Engineering, through its Industry 4.0 division, KERN IoP, contributes experience in sensing, data acquisition, monitoring, software and industrial process analysis. This combination matters because many production problems cross disciplinary boundaries and cannot be addressed through automation, materials science or software alone.

An important reference for our vision of i4Plas is the German tradition of Arbeitskreise, or technical working groups. In forums such as the working groups of Plattform Industrie 4.0, companies, trade associations and research institutions collaborate on pre-competitive issues including standardisation, interoperability, security and reference architectures. Even competing companies can exchange general methods, approaches and lessons learnt around a shared problem while protecting proprietary designs, processing parameters, formulations and other commercially sensitive information.

This model is highly relevant to Colombia’s plastics industry. Challenges such as scrap, energy efficiency, machine availability, data integration, traceability, use of recycled materials and workforce training are shared by many companies. Addressing them collaboratively helps the sector compare approaches, test technologies and develop technical criteria while each business protects its sensitive data and proprietary know-how. For KERN IoP, this potential for collaboration is a major reason for taking part in the creation of i4Plas.

Training the people who will operate tomorrow’s plants

Workforce training is equally pressing. The natural renewal of technicians, machine operators, supervisors and engineers coincides with the introduction of increasingly connected equipment, data-acquisition systems, analytics and artificial intelligence. When training lags behind, companies may acquire sophisticated technology without developing the skills needed to interpret and use it in production. Through i4Plas, we want to help the next generation of plant personnel work confidently with data, understand how digital systems operate and make informed engineering decisions about the process—not merely use tools configured by others.

Making effective use of these technologies requires a shared conceptual foundation among plant personnel and specialists. Our guide What is Industry 4.0, and how can it improve decision-making on the plant floor? examines the role of people alongside digital twins, simulation and advanced control.

KERN IoP’s role in i4Plas

At KERN IoP, we work at the interface between the physical process and its data. This covers sensing, acquisition of machine and auxiliary-equipment signals, monitoring of production variables, energy measurement and software that adds operational context to data for analysis.

Within i4Plas, our aim is to apply this experience to projects that can be tested and measured. Examples include assessing energy consumption by machine or manufacturing cell, tracking process variables, developing production indicators, tracing data and integrating information from different assets. On this website you can learn more about our industrial monitoring platform, our solutions for energy measurement and analysis and our work in injection moulding.

The value of i4Plas will depend on translating these capabilities into meaningful work for manufacturers: clearly defined problems, trials under real operating conditions, measurable outcomes, knowledge retained within participating companies and technical exchanges that help the sector learn more effectively.

Frequently asked questions about i4Plas

What is i4Plas?

i4Plas is the Centre for Digital Transformation in the Plastics Industry, established by Acoplásticos, ICIPC and KERN IoP to work with manufacturers on assessments, trials, pilot projects, training and the application of new technologies.

Which production problems will it address?

Initial focus areas include scrap and quality, unplanned downtime, energy consumption, traceability, circular economy applications and data integration. Technical training will also support effective adoption on the plant floor.

Which technologies can be evaluated?

Sensors, industrial IoT, data acquisition, analytics, artificial intelligence, machine vision, digital twins, robotics, additive manufacturing, energy measurement and traceability tools, among others. Selection depends on the problem to be solved.

Does a company need to digitalise the whole plant to begin?

A focused project involving one machine, one cell, one product reference or one specific need is often more useful. It provides a manageable way to measure outcomes, identify integration challenges and refine the solution before scaling.

Does every project require artificial intelligence?

Many problems first require reliable measurements, a coherent data structure or a correctly defined indicator. Artificial intelligence is appropriate when there is a clear use case, sufficient data and an objective means of evaluating performance.

What does KERN IoP contribute to i4Plas?

KERN IoP contributes expertise in sensing, acquisition and contextualisation of industrial data, machine and process monitoring, energy measurement and software development for plastics-processing plants.

References

ACOPLÁSTICOS – Asociación Colombiana de Industrias Plásticas. (2026, septiembre 29). La Industria 4.0 llega al sector plástico: lanzamiento de i4Plas durante ColombiaPlast 2026 [Publicación de LinkedIn]. LinkedIn.

ICIPC. (2026, septiembre 29). La Industria 4.0 llega al sector plástico: i4Plas, Centro para la Transformación Digital de la Industria Plástica [Publicación de LinkedIn]. LinkedIn. https://es.linkedin.com/posts/icipc_i4plas-industria40-colombiaplast2026-activity-7510383474554372097-Ciq8

Portafolio. (2026, septiembre 29). Industria plástica lanza el centro i4Plas para acelerar su modernización tecnológica. https://www.portafolio.co/negocios/industrias/industria-plastica-lanza-el-centro-i4plas-para-acelerar-su-modernizacion-tecnologica-503437

Envapack. (2026, septiembre 25). Nace i4Plas, el primer centro de transformación digital para la industria plástica en América Latina. https://www.envapack.com/2026/09/i4plas-transformacion-digital-industria-plastica/

Mitchell, D. (2026, septiembre 23). La IA también en la manufactura. La República. https://www.larepublica.co/analisis/daniel-mitchell-2608429/la-ia-tambien-en-la-manufactura-4488196

Tecnología del Plástico. (2026, septiembre 23). I4Plas: nace el centro de transformación digital para la industria plástica. Plastico.com. https://www.plastico.com/noticias

Líderes de Planta. (2026, septiembre 27). i4Plas: el primer centro 4.0 del plástico en LATAM llega a Colombia. https://lideresdeplanta.news/i4plas-el-primer-centro-4-0-del-plastico-en-latam-llega-a-colombia/

Revista Plastics Technology México. (2026, octubre 1). Publicación sobre i4Plas y su hoja de ruta para la transformación digital de la industria plástica [Publicación de LinkedIn]. LinkedIn. https://es.linkedin.com/posts/pt-mexico-revista_i4plas-activity-7511155490903486465-2uYp

Plattform Industrie 4.0. (s. f.). Die Arbeitsgremien der Plattform Industrie 4.0. https://www.plattform-i40.de/IP/Redaktion/DE/Dossiers/arbeitsgruppen.html