Informance GmbH

AT Technikum Wien

Industry 4.0Business Case

Workshop 21. November 2016 – Informance GmbH

Industry 4.0Informance GmbHCompany Profile, Timeline

● 2002 – Company Founding, industry focuses● 2004 – Introduction of „GlobalPlayer“ platform● 2010 – Launch of 1st Jungbunzlauer Austria AG project● 2013 – on-site launch of PAXAN● 2016 – Launch in Canada production site

Privately financed● Ing. Roman Ziehengraser, - 50% shares

Ing. Thomas Seitz - 50% shares

● ~15 employees at Vienna branch● Customers in Central Europe and Northern America

Industry 4.0Informance GmbHAbout us

Product Portfolio● GlobalPlayer platform for software, derrived solutions

Classic Software Engineering● Business Process Enineering● Enterprise Content Management● Mission Critical Systems

Strong Data Affinity ● Buillding TB databases 20yrs ago● Shaping the emerge of data

VSAM SQL OLAP BigData→ → →● Data driven projects and systems

Key Accounts

Industry 4.0The Business CaseIndustry 4.0 applied

Jungbunzlauer AGMarket leader in technical nutrition ingredients.

Challenging project EnvironmentHeterogenous production site, certifications, complex user requirements, interfaces to legacy systems, elements of IoT, ...

Steep learning curveRequires detailed knowledge about chemical processes.

Extensivly covered by NDA's :-(

Industry 4.0The ChallengeTurning ingredients into technical/nutritional products

Time-Consuming ProcessHard to keep track, challenging knowledge transfer

„Blackbox“Too complex to be thoroughly understood, many undocumented decisions, lass straight processes as expected

Creating Understanding● Learning about the informal and unspoken knowlegde of the employees● Structuring unstructured processes

Industry 4.0Phase 1From initial ingredients to intermediate product

Problems: ControlabilityProcesses hard to control, human flaws in process data

Solution: Interfaces, Documentation● Automated data transfer from measuring instruments● Graphs, data analysis helps to find unknown relations between process parameters

Future: Prediction● Machine learning determines the development of the product● Influencing the process as needed

Industry 4.0Phase 2From intermediate product to final product quality

Problems: Complexity, Uncertainties● Product does not remain „clean“ during the process● Process includes undeterministic elements● Complex system of relations and inclusions

Solution: Optimizing Workflows, Statistics● Error-prone Excel input vs graphical user interface with sophisticated templates● Few statistics, high amount of work vs many statistics, no work at all

Future: Automation● Humans: Semi-optimal, slow decisions● Software: Thousands of data sets, blink of an eye decisions

Industry 4.0User InterfaceCentral Intersection of Phases 1 and 2