15.7
trillion boost to the global economy is expected from AI by 2030
L A B O R AT O R I E S W I L L B E C O M E E S S E N T I A L N O D E S A N D S T R AT E G I C C O N T R O L U N I T S W I T H I N D ATA D R I V E N VA L U E G E N E R AT I O N
At Innovation Center nICLAS, members develop technologies for the smart lab of the future
ongoing loss of reliance on physical products, with a radical shift towards data-rich markets across most industry sectors. In this regard - especially for life science industries - laboratories will become essential nodes and strategic control units within data driven value generation. The future ‘laboratory’ might become a scientific data factory. Today, the concentration of expertise and knowhow in laboratories already leads to an increase in overall communication efforts and exchange. The increasing process complexities and dependencies tend to overwhelm traditional lab infrastructure and organisation. To challenge these side effects and avoid the setup of inefficient or redundant structures, a modern lab needs to match crucial key requirements. While classical paradigms such as platform automation, robotics or LEAN process optimisation frequently failed in the past, new organisational principles need to be defined. The laboratory, as an integral part of a connected company, primarily needs to
be adaptable, scalable and responsive to match the requirements and needs of a multitude of (external) stakeholders and services. Besides this customer-driven and service-oriented architecture, the lab needs to provide a robust, easy to maintain and easy-to-use set of tools, devices and processes to stay manageable and provide long-term sustainability. A kind of blueprint and design template to set up these principles can be seen in the general structures and principles of a city. While companies and business units tend to lose innovation power and efficiency at a certain level of growth, the decentralised organisation of Mega-cities attracts and generates unsuspected economical and innovation strength.
T H E H U M A N O P E R AT O R
A central requirement in the transformation of lab services into the nerve centre and holistic data hub of a data driven company is that of the human operator. Unlike other parts of the business, manual labour still accounts for major parts of lab process chains. Besides redundant and dull documentation or transportation tasks these operators and scientists perform an outstanding job by analysing complex data sets and deriving strategies and solutions. Biological process and non-standard, versatile process chains generate fragmented and interrupted information. The underlying combination of creativity and intelligence makes the operator a powerful and crucial element of the digitally interconnected smart lab of tomorrow. While modular and selfsufficient robotic systems, as well as artificial intelligence, will empower and foster data generation and evaluation, the complex interplay and ecosystem of human-machine, human-process, human-data and machine-data interactions will continue to require organisation and assistance.
R E A D O N L I N E AT: U K S PA . O R G . U K / B R E A K T H R O U G H
ADAPTED ASSISTANCE SYSTEMS
Nonetheless, the human brain capacity and potential to survey huge amounts of data is strictly limited. The critical and timesensitive challenge is to provide smart and adapted assistance systems to empower the human operator. The first step within this endeavour will be to establish a holistic understanding around the behavioural aspects and stress associated with lab work. The technological base for smart sensor systems is already available in sport training apps. A good second step would be to embed the operator in a framework of sensor-driven scene-analysis and smart control interfaces to analyse speech, gesture and context. Thus, a cyberphysical ecosystem of partly automated services emerges with the operator as node and main context provider. The third, and most important step, concerns a fundamental mind-shift within the lab community. Besides additional communication tasks and consulting services, the lab needs to establish a profound technological and data processing expertise.
AN ESSENTIAL IDENTITY SHIFT
Global data-driven companies such as Google, Amazon or Facebook already incorporate data generation and data processing capabilities and technologies. However, current business frameworks for responsible lab managers and operators ensure they identify themselves as working within a science-driven unit. The shift towards identifying as a techdriven unit will be crucial for the entrusted operators and the lab as a whole. Failing that, the aforementioned data-driven players or competing approaches from China may change or eliminate the laboratory as we know it. â–
For further information, visit: www.ipa.fraunhofer.de/niclas
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