CEO & founder Benjamin Brockmann (M. Sc., Management & Technology) founds cioplenu GmbH in 2017 together with Daniel Grobe (also M. Sc., Management & Technology). The founders develop the software solution on the basis of various practical projects, including at the Fraunhofer Institute, and their experience in industry, auditing and management consulting. Benjamin Brockmann has already worked for companies such as KPMG and Arthur D. Little.
More efficiency and better decisions with smart workflows
by Benjamin Brockmann | 20th October 2020
I always find it fascinating to dive into the production of our customers or other manufacturing companies. The professionalism and excellence that both medium-sized and large companies have acquired over many decades impresses me enormously. Unbelievable dynamics of laser cutting robots, lightning-fast tool changes in milling machines, very competent and committed employees.
But what amazes me at the same time is the often still very analogous way of working when it comes to processes that do not directly add value to the product. By this, I mean processes such as maintenance work, inspections or even analyses. If, for example, a tolerance deviation occurs in the quality inspection, we meet to investigate the cause. As a consequence, pictures are taken of the faulty workpiece and these are hung up in the assembly department to avoid such errors. From my point of view, not a smart workflow.
The ambition of smart workflows
It’s time to take a closer look at smart workflows in the production environment. The goal here should be to start an automated process based on defined trigger events and general conditions. This process should not only inform all relevant stakeholders, but also be based on digital tools to make better decisions.
Let’s transfer the idea to the above example from quality inspection: During visual inspection in a digital tool, the employee is automatically requested to record an error image if the tolerance is exceeded. Based on the defined workflow, this error image is automatically transferred to a system that uses artificial intelligence to determine the causes and develop suggestions for quality measures across all locations. The quality manager also sees in real time on his dashboard that a defect has occurred and is added to the automated e-mail that is sent to the Six Sigma expert. The expert is assigned to analyze the problem in more detail and is provided with further process parameter information. The customer order, on the other hand is reported as ‚delayed‘ in the ERP so that the account manager can work on alternative solutions with the customer as a preventive measure.
Our cioplenu process experts will be happy to advise you on the current possibilities for implementing smart workflows
All around, smart workflows should help to provide real-time information to all relevant people and systems to make better decisions. In the example of quality assurance, this means less effort for transactional communication, ensuring the provision of information, and ultimately higher customer satisfaction through proactive solution finding.
What are smart workflows?
Automated workflows are relatively widespread. An event triggers an activity. An e-mail is triggered based on a finding. Although there is currently no common definition of smart workflows. However, what distinguishes smart workflows from purely automated, comparatively trivial workflows, in my view, is the mapping of organizational complexity and thus, the linking of several IT systems and the consideration of general conditions.
The technical basis for this is formed by three process levels:
1) Integrated software in operational use
At shop floor level, employees use software that offers customizable trigger events (problem in a checklist, recording of an error image) and can pass these on via an open interface (API, Webhooks). This software thus represents the starting point for smart workflows.
2) Workflow level for building customer-specific process flows
In order to realize individual workflows dynamically, a “Logic-Layer” is needed, which allows to create and develop workflows and decisions in a comprehensible way. In the past, scripts were created by IT departments for this purpose. Those are rather time-consuming to maintain and are not comprehensible to third parties. In today’s generation of solutions, automation platforms are used to create workflows using the drag & drop principle. This allows the logic component of smart workflows to be created in a user-friendly way.
3) Third party software for messaging, analysis and process mining
Last but not least: third-party software, which is triggered from the “Logic-Layer”. For example, the logic layer can initiate the sending of an e-mail or enter the resulting checklist data into a process mining tool. By process mining, we understand the structured evaluation of time stamps and data points for the actual execution of a process and the subsequent comparison against a target process to identify optimization potentials. In the example of quality control, it would be possible to measure how often an executed process did not comply with the standard, which actual work steps were carried out and why.
In short, an end-to-end automated flow of information across all three process levels shortens reaction times enormously and creates process transparency.
The added value
I am convinced that increasing the speed of decision-making processes is a central imperative of Industry 4.0. The goal should be that not only the travel speed of welding robots and machine tools increases, but that the human decision process is supported by digital tools. Thus, decisions can be made faster because information is immediately available. Better decisions can be made because the quality of information is significantly higher. And finally, enormous effort is saved because processes such as error image storage are fully automated.
It is true that smart workflows as described above can largely be mapped by standard software. But in my view, it is extremely important to ensure a balance between business value and complexity. This means that all workflows should represent a clear added value for the company. So, before the software is implemented, the smart workflows should be defined at the business level with relevant stakeholders such as the business department, IT, project departments and the sponsor.
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