Advisory Board

Dr Samer Aljishi

President, BFG International

Dr. Samer serves as the President of BFG International. Dr. Samer joined the firm in 1992 and took over management at BFG International and oversaw its growth and development into a world-class manufacturing and engineering firm.

From 1990 to 1992, Dr. Samer advised the Minister of Industry in Bahrain on industrial development. He is the Member of Board of Directors of Bahrain Mumtalakat Holding Company B.S.C., Gulf Air, the Bahrain Economic Development Board, BFG International and Ilium. Dr. Samer served as a Director of Gulf Air Company G.S.C.

Sir Tim Berners-Lee

Professor, Massachusetts Institute of Technology

Sir Tim Berners-Lee invented the World Wide Web in 1989. He wrote the first web client and server in 1990. His specifications of URIs, HTTP and HTML were refined as Web technology spread.

Sir Tim is the Director of the World Wide Web Consortium (W3C), which oversees the technical standards development of the Web.

Sir Tim is the founder and a Director of the World Wide Web Foundation which was launched in 2009 to coordinate efforts to further the potential of the Web to benefit humanity.

He is a Professor at the Massachusetts Institute of Technology (MIT) where he co-leads the Decentralized Information Group (DIG). He is also a Professor in the Computer Science Department at the University of Oxford, UK. He is President of and founded the Open Data Institute in London.

In 2017, Sir Tim was awarded the ACM A.M. Turing Prize, called the “Nobel Prize of Computing” and considered one of the most prestigious awards in Computer Science.

Dick Cashin

CEO, One Equity Partners

Dick Cashin founded One Equity Partner in 2001 and is the President based in New York and a member of the Investment Committee.

Dick has over 36 years of private equity investing experience and a strong performance track record across various industries and markets. He has been closely involved in all of OEP’s prior investments and was a member of the Investment Committee during OEP’s 14 years within JPMorgan. Dick is a member of the Board of Directors of Genband and Titan International.

Prior to founding OEP, Dick was with Citigroup Venture Capital from 1980-2000 and served as President from 1994-2000. He is a Trustee of the American University in Cairo, Boys Club of New York, Brooklyn Museum, Central Park Conservancy, Jazz at Lincoln Center, National Rowing Foundation, and Newport Festivals Foundation. Dick is active in inner-city educational initiatives, Harvard fundraising and has served as Co-Chairman of his Harvard class for over 35 years. In 1976 and 1980, Dick was a member of the U.S. Olympic Rowing Teams and was a world champion in 1974. Mr. Cashin is the son of a Foreign Service Officer and grew up in Libya, Ethiopia, Ghana, Indonesia, and Pakistan.

Dick attended Harvard University and graduated in 1975 with a degree in East Asian Studies. Following a one-year fellowship at Trinity College, Cambridge in 1976, he worked at Jardine Matheson in Hong Kong. In 1980, he completed his M.B.A. at Harvard Business School.

Carl-Peter Forster

Carl-Peter Forster started his career at McKinsey & Company as a management consultant in 1982. After four years, he joined BMW in Munich, becoming a member of the Executive Board in 1999 as Head of Global Manufacturing.

In 2001, he joined the European division of General Motors and became Managing Director of Opel and Vice President of GM Europe. In 2006 he became CEO and President of GM Europe and joined the parent company’s Global Automotive Strategy Board. After leaving General Motors, he became Group CEO at Tata Motors, including full responsibility for the Jaguar Land Rover.

From 2013 to 2019, Carl-Peter Forster was Special Advisor to the Chairman of the Geely Group, holding board positions at Volvo Cars Group, Gothenburg, Geely Automobile Holdings Ltd, Hong Kong, as well as CEVT, the Geely engineering centre in Gothenburg and Chairman of The London Electric Vehicle Company (formerly The London Taxi Company)

Carl-Peter Forster is currently Chairman of Chemring Plc, Chairman of the Shareholder Committee of Hella KGaA; and a member of the boards of IMI Plc., Babcock Plc, The Mobility House AG, Gordon Murray Design Ltd., Kinexon GmbH, Clear Motion Ltd., Envisiscs Ltd., and LeddarTech Ltd.

Baz Khuti

Co-founder and Strategic Advisor

A technology and business visionary, Baz has held executive leadership positions at GE (CTO Cloud), Emerson Electric (EVP, Emerson Network Power; Chief Architect, Emerson Electric) and Invensys, now part of Schneider (Chief Architect). Baz has brought to market leading software products from idea to industry standard, with six industrial software patents and winning a number of prestigious industry awards.

With over 30 years of technology experience across the UK, US and Asia Baz has a proven track-record of developing software platforms and industrial applications at scale through the architecture and design of pioneering technologies. Baz holds a MSc in computer science.

Rick Ledgett

Director, M&T Bank

Rick has four decades of intelligence, cyber security and cyber operations experience, including 29 years with the National Security Agency (NSA), the largest intelligence organization in the U.S., where he served as Deputy Director from January 2014 until his retirement in April 2017. In that capacity, he led a global entity with almost 200 operating locations around the world and acted as the Agency’s chief operating officer, responsible for providing foreign intelligence and protecting the nation’s most important national security-related networks and information.

Rick led NSA’s Media Leaks Task Force, responsible for the totality of the Agency’s efforts following the unauthorized disclosure of classified information in June 2013. He also led the NSA’s 24/7 Threat Operations Center (NTOC), responsible for identifying and countering cyber threats to our national security systems. Rick was the Intelligence Community’s first National Intelligence Manager for Cyber, serving as principal advisor to the Director of National Intelligence on all cyber matters. In this capacity, he was responsible for integrating cyber activities across 16 intelligence agencies and numerous international partners, and he developed the first National Intelligence Strategy for cyber. He was also the DNI’s Director for Collection, overseeing all of the Intelligence Community’s collection programs.

Previous jobs at NSA included leading global collection and cryptanalytic operations, global language and analytic operations, and all NSA activities in the Pacific area. He was an instructor and course developer at the National Cryptologic School and an adjunct instructor at the National Intelligence University. Rick spent nearly 11 years in the U.S. Army and completed six field tours between the Army and the NSA.

Rosemary Leith

Non-Executive Director, YouGov PLC

Rosemary is a Non-Executive Director of YouGov plc, an international online Market Research and Data Analytics company. She also currently advises and invests in a number of technology businesses in Europe and North America including those operating in the Data Analytics, Internet of Things and Financial Technology arenas.

Rosemary is a Trustee of the National Gallery (London) and a Fellow at Harvard University’s Berkman Center for Internet & Society, most recently authoring an Executive Education Course for Board Chairs and Non-Executive Directors on CyberSecurity.

Rosemary has been the Chair of the World Economic Forum Global Agenda Council on the Future of Internet Security and is a member of the Advisory Boards of Infinite Analytics (Boston and Mumbai), Glasswing Capital (Boston), a Member of Raspberry Pi Foundation (overseeing commercial operations of Raspberry Pi), Queen’s University School of Business, Canada, Wolfson College, Oxford and University of the Arts London. She is a regular attendee and contributor to TED and the World Economic Forum.

DEUTSCHE

Die vierte industrielle Revolution, oder Industrie 4.0, ist gekennzeichnet durch das intelligente Vernetzen von Maschinen, Produkten und Mitarbeitern mit cyber-physikalischen Systemen in intelligenten Fabriken. Die Produktion in intelligenten Fabriken wird hochflexibel. Die Optimierung der Wertschöpfungskette erfolgt darin basierend auf Echtzeit-Anforderungen, Mitarbeiter werden von intelligenten Kontrollsystemen profitieren. In der intelligenten Fabrik wird die Kombination aus Material, Lieferanten, Ausrüstung und qualifizierten Mitarbeitern so organisiert, dass sie Einheiten produzieren, die den Kundenanforderungen in Echtzeit genügen. Die Personalisierung auf Kunden- und Marktsegmente wird durch integrierten Bedarfssignale gewährleistet, um skalierbare Geschäfte zu erzielen. Die intelligente Fabrik erfordert eine flexible und agile vernetzte Produktion.

Flexibilität bedeutet, dass die Betriebsmittel in der Lage sein müssen, eine Vielzahl unterschiedlicher Produktionsprozesse durchzuführen. Die Mitarbeiter müssen über ein sehr breites Spektrum an Qualifikationen und Erfahrungen im Umgang mit verschiedenen Systemen und Methoden verfügen.

Darüber hinaus erfordert die Flexibilität eine sehr hohe Verfügbarkeit der Einsatzmittel. Vernetzt bedeutet, dass alle relevanten Informationen für die Herstellung eines Produkts in Echtzeit zwischen allen Systemen und den am Prozess beteiligten Personen ausgetauscht werden. Tritt beispielsweise bei kritischen Anlagen ein Fehler auf, müssen neue Wege durch die Produktion gefunden werden, um Aufträge termingerecht zu erfüllen. Um das zu erzielen müssen alternative Arbeitspläne und die daraus resultierenden Produktionskosten und -zeiten analysiert werden. Neue Produktionseinheiten entstehen durch die neue Kombination von Ressourcen, Ausrüstung und Personal pro Auftrag. Dies erfordert eine enge Interaktion zwischen Ausrüstung, Ressourcen und Mitarbeitern mit einem intelligenten Produktionssystem, das sowohl die alternativen Routen als auch die Produktionskapazitäten verwaltet. Daher ist die Integration von Daten aus verschiedenen Systemen intern und extern unerlässlich.

Ziel dieses Forschungsprojekts ist es, Techniken zur Realisierung schlanker intelligenter Fabriken zu entwickeln, umzusetzen und zu validieren:

Das erste Projektziel ist die Entwicklung von neuen Algorithmen die den aktuellen Zustand der Fabrik bei der Erstellung des Produktionsplans berücksichtigen.

Das zweite Projektziel ist die Entwicklung einer Methodik für das Lösen von Systemen mit multiplen und teilweise probabilistischen Randbedingungen basierend auf reinforcement learning techniques.

Das dritte Projektziel ist es, eine mathematische Darstellung des genauen Zustands und Verhaltens der Produktionsanlagen zu generieren, die QiO den PARCS score nennt.

In diesem Arbeitspaket werden hochdimensionale teilweise diskrete Optimierungsprobleme mit einer Vielzahl von Nebenbedingungen mit modernen mathematischen Verfahren bearbeitet.

ENGLISH

The fourth industrial revolution, or Industry 4.0, is marked by the intelligent networking of machines, products and employees with cyber-physical systems in Smart Factories. Production in Smart Factories will be highly flexible, highly productive and resource efficient. The optimization of the value chain is based on real-time requirements. At the Smart Factory, the combination of materials, suppliers, equipment and skilled employees is organized to produce units that meet customer demands in real time. Personalization to customer and market segments is ensured by integrated demand signals to achieve scalable business.

The Smart Factory requires flexible and agile networked production. Flexibility means that the operating resources must be able to carry out a variety of different production processes. Employees are required to have a very broad range of qualifications and experience in using different systems and methods. Furthermore, flexibility requires a very high availability of operating resources.

Networked means that all the relevant information for the manufacture of a product is shared in real-time between all of the systems and people involved in the process. This requires information about potential machine breakdown, delays to a supplier order, missing parts, personnel availability or available skills.

If a fault occurs to critical piece of equipment, for instance, new routes through production must be found in order to fulfil orders on time. In order to do this, alternative work schedules and the resulting production costs and times must be analysed. New production units arise through the new combination of resources, equipment and personnel per order. This requires close interaction between equipment, resources and the workforce with a master intelligent production system, which manages the alternative routes as well as production capacity.

As such integration of data from diverse systems internal and external is therefore essential. The aim of this research project is to develop, implement and validate techniques for the realization of Smart Factories:

The first project objective is the development of new algorithms that take into account the current state of the factory when creating the production plan.

The second project objective is the development of a methodology for solving systems with multiple and partially probabilistic constraints based on reinforcement learning techniques.

The third goal of the project is to generate a mathematical representation of the exact condition and behaviour of the production facilities, which QiO calls the PARCS™ score. It is designed to enable engineers within software tools such as the QiO Foresight Engine™.

This work package deals with high-dimensional, partially discrete optimization problems with a variety of constraints using modern mathematical methods. The results of the project proposed here go well beyond the general state of the art, especially in the fields:

Artificial intelligence for the dynamic learning and modeling of production processes

Artificial intelligence for production planning and supply chain management

Traditional approaches to modeling and describing production processes assume a well-known problem and seek a solution to a specific problem. This approach is not suitable for solving such problems in the context of an intelligent factory. The boundary conditions that describe the processes change regularly here and they are mostly of a probabilistic nature. We plan to learn the processes dynamically based on the data produced by a production hall. We call such dat, the voice of the production hall.

Such automated learning is important because constructing a graphical model by a human expert can be cumbersome and time-consuming. If, as is often the case, there is a database of examples, learning techniques can do at least part of the work. This approach should lead to an always current and dynamic view on the production processes. It should also form a mathematical basis for dynamic production planning as it will be described in the next.