Stratum 4 – Engineering Intelligent Automation Systems

Welcome to Stratum 4’s website. We are a professional consultancy dedicated to assisting industrial clients with innovation in the digital age, providing guidance on the architecture and engineering of intelligent (cognitive) industrial automation (IA) systems and services.

Stratum 4 Brochure is available here.

In advancing production efficiencies, productivity, and security in a broad range of industrial settings, IA systems employ enterprise-level architectures and operational strategies for automating the monitoring, analysis, supervision, and regulatory control of real or synthetic value production processes.

Intelligent IA systems produce and consume exponentially expanding data sets requiring application of computational (data) science and systems engineering. This includes artificial intelligence (machine learning), secure time-sensitive networks, cloud storage systems and the continuous analysis of processes involved in data management, situation assessment, decision, and adaptive control applications.

Industry 4.0 defines a contemporary smart manufacturing strategy that supports coupling disparate legacy business and manufacturing systems with advanced IA systems. Together they provide integrated production automation services through secure, distributed, time-critical automation utilizing intelligent Industrial Internet of Things (IIoT) edge devices integrated into advanced Cyber-Physical Systems (CPS).

Caveat 1:  To paraphrase Bruce Schneier (CTO, IBM Resilient) in his January 27, 2017, New York Magazine essay "Click Here to Kill Everyone," there are compelling reasons to temper, if not in some cases reverse, the tendency to connect anything and everything to the Internet.

An unbridled IoT phenomenon, especially in automating industrial systems, contains a host of thorny unresolved issues concerning, among other technical, social and political concerns, matters of the reliability, privacy, safety, performance, integrity and accountability of resultant systems.

At the end of the 20th century, we lived in a world of things, some with attached or embedded computers. At the beginning of the 21st century, punctuated by the 2007 emergence of the computationally powerful, mobile, and now ubiquitous smart phone, we entered a world defined by computers with a growing number and variety of software-enabled things attached to them.

Where products previously contained less than 20% of their functionality defined in software, today it approaches 80%. Refrigerators are now computers with compressors that cool stuff. Ovens are computers that heat stuff. TVs are computers for interacting with streamed digital content. ATMs are computers dispensing currency – real and virtual. Cars are computers (actually, mobile networks of computers) connected to engines and wheels that move stuff. Power plants are computers that electrify stuff. Hospitals are computers, embedded with nurses, physicians, and diagnostic devices, all for administering “health.” Factories are computers that make stuff, and enterprises are computers that convert value propositions to capital.

With this shift in paradigm the Internet is no longer simply (wondrously!) a packet-switched communications platform. It has become a global, distributed “cloud” computer, large, growing and decentralized, attached to an incredible array of software-defined “things” that alone and in concert act as “computational service systems” for the purpose of automating any physical or synthetic process that can be exactly specified.

Emerging Industry 4.0 solutions enable enterprises of arbitrary size to operate as Decentralized Industrial Organizations (DIO)., where individual DIO are collaborative members of permissioned peer-peer value production networks (e.g., supply chains) without need of a central authority. They increasingly employ artificial intelligence (AI) applications to implement trusted, resilient, and agile supply chain management regimes, resulting in the production and sharing of large operational datasets (e.g., via data warehouses and distributed ledgers). Consequently, DIO must share cybersecurity (e.g., authentication and audit) policies and mechanisms, internally and among their collective behaviors, qualified by shared operational imperatives and governing algorithms (e.g., smart contracts.)

DIO are naturally linked horizontally along producer-consumer (supply) chains and vertically along superior-subordinate (accountability) chains. They are intelligent (cognitive) to the degree they continuously maintain awareness of, and predictable performance in response to a range of situations unfolding within their operational ecosystems. Further, DIO may be stationary or mobile (in cyberspacetime), whether their services are embedded as components in other systems or function independently as distributed “end systems” at the edge of large-scale cloud-hosted service systems.

Caveat 2: Be aware!

As a professional advisory practice, Stratum 4 provides fractional CTO-class experiences and capabilities related to technical due diligence (M&A), training, R&D partnerships, and program management. Successful development and deployment of intelligent automation systems requires systems science (cybernetics), data science, distributed systems (secure, real-time, high performance and high availability computing, storage, and communication systems), and applied mathematics (dynamic systems modeling, simulation, and visualization).

Stratum 4 is dedicated to assisting clients with strategy, design, development, operation and maintenance of intelligent products and service systems.