Configuration Management Through Satisfiability

Pearce, Bryan; Kurz, Mary E.; Phelan, Keith; Summers, Joshua D.; Schulte, Jörg; Dieminger, Wolfgang; Funk, Kilian

doi:10.1016/j.procir.2016.02.127

Cited by 2 publications

(3 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Based on the existing configuration approaches discussed earlier in the work, four support tools are recommended to assist in the configuration management process at the automotive OEM. Prototypes for all tools have been provided to the OEM and have been preliminarily vetted for further refinement and deployment (Phelan, Summer, Pearce and Kurz, 2015a; Phelan, Wilson, Joshua and Mary, 2015, Phelan, 2016; Pearce et al , 2016). In order to support the other tools that are recommended, the first step is to develop an interaction identification tool that will allow the user to view how changes to the rule database will propagate through the system and affect other rules.…”

Section: Discussionmentioning

confidence: 99%

“…The AV tool uses a satisfiability tool to determine whether any conflicts will arise as a result of a proposed change being implemented. The tool allows the user to evaluate the current rule system to determine if there are any conflictions or other errors (Pearce et al , 2016). The additional errors that can be evaluated are whether components or options are actually able to be called for a specific model, if specific rules can be activated or if they are unnecessary and the determination if any component from a component family meet specific criteria (such as only one windshield being available at a time).…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Configuration and options management processes and tools: an automotive OEM case study

Phelan

Summers

Kurz

et al. 2017

JMTM

Self Cite

View full text Add to dashboard Cite

Purpose The purpose of this paper is to propose a three-staged approach to configuration change management that uses a combination of complexity analysis, data visualization, and algorithmic validation to assist in validating configuration changes. Design/methodology/approach In order to accomplish the above purpose, the authors conducted a review of existing configuration management practices. This was followed by an in-depth case study of the configuration management practices of a major automotive OEM. The primary means of data collection for the case study were interviews, ethnographic study, and document analysis. Based on the results of the case study, a set of support tools is proposed to assist in the configuration management process. Findings Through the case study, the authors identified that the OEM used a configuration management method that largely represented the rule-based reasoning methods identified in the literature review. In addition, many of the associated challenges are present, primarily, the difficulty in making changes to the rule system and evaluating the changes. Research limitations/implications The primary limitation is that the case study was based on a single OEM. However, the results are in line with other practices identified in the literature review. Therefore, it is expected that the findings and recommendations should hold true in other applications. Practical implications A set of configuration management tools and associated requirements are identified and defined that could be used to assist companies in the automotive industry, and perhaps others, in managing their option changes as they continue to move towards full mass customization of products. Originality/value The proposed approach for configuration management has not been seen in any other organization. The value of this paper is in the effectiveness of the proposed approach in assisting in the configuration change management process.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Configuration and options management processes and tools: an automotive OEM case study

Phelan

Summers

Kurz

et al. 2017

JMTM

Self Cite

View full text Add to dashboard Cite

show abstract

“…Representing implicit knowledge by using a set of rules containing the Satisfiability (SAT) is a powerful strategy in solving various industrial problems. Recently, SAT representation has been proposed in mathematical modelling [23], model checking [24] and industrial management [25]. SAT is an important language that can store important information which leads to two possible outcomes (True or False).…”

Section: Introductionmentioning

confidence: 99%

Systematic Boolean Satisfiability Programming in Radial Basis Function Neural Network

et al. 2020

View full text Add to dashboard Cite

Radial Basis Function Neural Network (RBFNN) is a class of Artificial Neural Network (ANN) that contains hidden layer processing units (neurons) with nonlinear, radially symmetric activation functions. Consequently, RBFNN has extensively suffered from significant computational error and difficulties in approximating the optimal hidden neuron, especially when dealing with Boolean Satisfiability logical rule. In this paper, we present a comprehensive investigation of the potential effect of systematic Satisfiability programming as a logical rule, namely 2 Satisfiability (2SAT) to optimize the output weights and parameters in RBFNN. The 2SAT logical rule has extensively applied in various disciplines, ranging from industrial automation to the complex management system. The core impetus of this study is to investigate the effectiveness of 2SAT logical rule in reducing the computational burden for RBFNN by obtaining the parameters in RBFNN. The comparison is made between RBFNN and the existing method, based on the Hopfield Neural Network (HNN) in searching for the optimal neuron state by utilizing different numbers of neurons. The comparison was made with the HNN as a benchmark to validate the final output of our proposed RBFNN with 2SAT logical rule. Note that the final output in HNN is represented in terms of the quality of the final states produced at the end of the simulation. The simulation dynamic was carried out by using the simulated data, randomly generated by the program. In terms of 2SAT logical rule, simulation revealed that RBFNN has two advantages over HNN model: RBFNN can obtain the correct final neuron state with the lowest error and does not require any approximation for the number of hidden layers. Furthermore, this study provides a new paradigm in the field feed-forward neural network by implementing a more systematic propositional logic rule.

show abstract

Configuration Management Through Satisfiability

Cited by 2 publications

References 13 publications

Configuration and options management processes and tools: an automotive OEM case study

Configuration and options management processes and tools: an automotive OEM case study

Systematic Boolean Satisfiability Programming in Radial Basis Function Neural Network

Contact Info

Product

Resources

About