P-Diagram or Parameter diagram for system analysis has its history from the Six Sigma methodologies for quality management for reducing defects and variations in a product. This has been widely used in system analysis for automotive systems. The classical P-diagram that has been used in the industry focuses mainly on three parameter groups. They are input parameters, output parameters, and noise parameters. Beyond these three groups, for analysis purposes, there are certain control factors and the error state that the system will experience under certain conditions where the input or noise parameters influence the normal operation of the system.
P-Diagram became popular and is widely used in the market mainly as an easy-to-use tool to create an interrelationship between the input parameters, noise parameters, and the system's output. Considering the DMAIC framework from six sigma for problem-solving to systems engineering for product design and analysis. There are a few relevant inputs that would help improve the system design by detailed analysis and considering the factors such as noise and input parameters fed into a system. This is because an automotive system that is under design will be integrated and operated into a more extensive system as the concept of System-of-systems. The operational environment is one of the key elements that determines the regular operation of the system. The Six Sigma concept, which was initially developed considering the quality of the manufacturing processes and their optimization for better yield, can be thus applied to a system during its analysis in the development phase.
The DMAIC method application in the system analysis will help derive the error state or the failure state of the system and the factors or parameters that can be optimized to control the output of the system under various changes in input parameters and during the influence of the noise factors that are triggered from the operational environment of the system. These triggers can be either from other systems that are operating in tandem with the system, by the environment, or by the operational ecosystem itself. A classical P-diagram looks like the one below, where the input parameters are considered as the output, the different noise factors, Error states, and the control factors with which the system operation can be controlled to provide optimized output in the functionality and performance.
Designing a robust system that operates over various conditions that it experiences over its lifetime is well analyzed with this method using Parameter Diagrams. The noise factors that are usually considered for a system can still be grouped under i) Piece to piece variation – that is, usual variation of the products as an outcome from the manufacturing line, ii)System change over time – considering the change is system characteristics over prolonged usage or over time, iii) Conditions of the external environment – different environmental conditions, those impacted with the weather, iv) Interaction with other systems and subsystems and v) the usage conditions by the customer including misuse conditions.
The evolution of technology brought in changes in the environment and the influencing parameters associated with changing environments. One cannot consider a system with any connectivity these days in the automotive environment. The connectivity can be wired or wireless, allowing the system to exchange data and information with its partnering systems or the environment. This can be considered as part of the input parameters of the system.
Still, connectivity provides a bi-directional information exchange that includes data input, output, and control signals that monitor and manages the system. Applying traditional methods and the classical approach of P-Diagram for system analysis will not help to cover the overall operational phase of the system, considering the changing ecosystem these days. The connectivity by wired or wireless mechanisms brings a lot of vulnerabilities to the system if the connectivity and the data flow are not secured to control external interference.
Cyber-physical systems these days, with a lot of connectivity and data exchange to external systems and infrastructure, have a lot of vulnerabilities associated with it. Attackers can utilize connectivity and associated vulnerabilities of the system to manipulate the system functionalities and its performance and even drive the system to various error conditions that will not get usually be analyzed as part of the traditional approach of system analysis using a Parameter diagram. Cyber attacks using vulnerabilities in the system have increased these days with the adoption of new technologies and a high level of system connectivity.
Hence there needs to be an improvised version of the P-diagram required for analysis to address the changing ecosystem to perform the overall system analysis, including the attacks that the system must consider and preventive actions to be taken. The figure shows the improved P-diagram that addresses the need to analyze the cyber attacks that can be associated with the complex cyber-physical systems using the vulnerabilities via different connectivity interface that helps the analysis phase of the system design and development.
An example below shows how the improved P-diagram can be used to analyze a system such as a camera module for an ADAS system in the vehicle. Readers can use this as a reference to start preparing for their analysis next time when designing a system that needs to be robust and should handle the cybersecurity attacks experienced in cyber-physical systems.
* More analysis and methods for ADAS system design and testing can be found in my book
'ADAS and Automated Driving - A Practical Approach to Verification and Validation '
https://www.sae.org/images/bookstore/r-525/
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