People-Centred Productivity (PCP)

What is PCP and what are its origins?

Over the last decade Industry 4.0 has been the subject of intensive research efforts in digital manufacturing and heavy investment support by the public and private sectors. Most developments in this area have focused on technology-oriented manufacturing and in the related megatrends such as robotics, computer-integrated manufacturing and cyber-physical systems (CPS), which are re-shaping how industrial production is seen and understood.

In order to understand the Industry 4.0 opportunities manufacturers need to understand and maximise the value of their people by developing the right skills to see the potential value in the current and future business models.

We have an opportunity to harness the potential of Industry 4.0 technologies to the benefit of the UK, global economy and society and to ensure that we can all trust and rely on technology to support our future societal and environmental sustainability.

However, in order to harness this potential, we need to develop a better understanding of human complexity and better methods to ensure that new technologies being developed are trustworthy and adoptable by embedding human and societal values throughout the technology lifecycle.

To do so, we need new fundamental and applied research groups which cross disciplinary boundaries and meaningfully bring together social sciences, humanities, engineering and computer sciences to better understand how to maximise the benefit to society and the economy.

This research also needs to go beyond academia and recognise that innovation activities across application domains are interlinked and interdependent on each other to realise the full socioeconomic benefit of Industry 4.0.

What is AME doing to address it? How is this different from other organisations?

PCP combines the transdisciplinary knowledge of computer scientists, designers, industrial engineers, with those of psychologists and social scientist to concentrate on the means by which technologies can be designed and implemented for humans, rather than being seen as an afterthought. These people factors are now ripe for addressing a major issue in UK manufacturing by investigating the role of people in the context of productivity.

The PCP research takes place within a cross-disciplinary research environment, engaging scientists and practitioners possessing critical skills and competences required to advance knowledge in this field. AME is taking this initiative at a time when change is urgently needed to boost and sustain recovery from unprecedented financial pressure on industry in the manufacturing sector and beyond.

• Our transdisciplinary team

  Key Staff from Leading Institution	Area and Discipline
  Dr Marcos Kauffman	Technology & Law - Social Sciences
  Professor Ann-Marie Nienaber	Human Resources - Social Sciences
  Dr Lorena Moreira	Manufacturing - Engineering
  Professor Benny Tjahjono	Sustainability - Social Sciences
  Dr Rosamaria Cisneros	Dance - Arts and Humanities
  Professor Scott Delahunta	Dance - Arts and Humanities
  Professor Trevor Toman	Metrology and Sensing
  Professor James Brusey	Computing - Computer Sciences
  Dr Andre Soares	Organisational Psychology - Social Sciences
  Professor Guy Daly	Learning and Well-being - Social Sciences
  Professor Stewart Birrell	Design and human factors - Engineering
  Professor Maureen Meadows	Strategic Management - Social Sciences
  Professor Dobrila Petrovic	Supply Chain
  Professor Kuo-Ming Chao	Computing - Computer Sciences
  Dr James Shuttleworth	Digital Maturity and Cyber Security
  Dr Richard Lane	Digital Maturity and Immersive technologies

   

What are we hoping to achieve?

PCP aims to explore the opportunities and challenges of this intersection between people, technology, businesses and society across a range of short, medium and long-term research questions. The team works on applied solutions co-created with our partners at AME.

Our research team will generate and test people-centred interventions, strategies, frameworks, and solutions (e.g. technology) that increase the effectiveness of technology deployment and productivity in general. Existing methods applied in computer science, social science, engineering and applied mathematics will be adapted and new methods will be developed, such as machine learning methods, cognitive maps and case-based reasoning approaches. These will be combined with methods commonly applied in social sciences, arts, humanities and neurosciences.

This group will provide a platform for change, to advance, combine and disseminate methodological and theoretical knowledge in engineering, business management, computer and behavioural sciences. It will further challenge traditional research approaches and business practices and achieve productive, environmentally sustainable, connected supply chains, enhanced worker behaviours and socially sustainable industrial models.