C. Del Valle

Automatic assembly task assignment for a multirobot environment

Abstract This paper presents an algorithm A ∗ for obtaining the “best” assembly plan for a product in a multirobot system. The algorithm takes into account, in addition to the assembly times, the times needed to change tools in the robots. The objective of the plan is the minimization of the makespan. To meet this objective, the algorithm starts from the And/Or graph (compressed representation of all feasible assembly plans) and the information on each assembly task (robot and tool needed, and assembly time).

Diagnosing errors in dbc programs using constraint programming

Model-Based Diagnosis allows to determine why a correctly designed system does not work as it was expected. In this paper, we propose a methodology for software diagnosis which is based on the combination of Design by Contract, Model-Based Diagnosis and Constraint Programming. The contracts are specified by assertions embedded in the source code. These assertions and an abstraction of the source code are transformed into constraints, in order to obtain the model of the system. Afterwards, a goal function is created for detecting which assertions or source code statements are incorrect. The application of this methodology is automatic and is based on Constraint Programming techniques. The originality of this work stems from the transformation of contracts and source code into constraints, in order to determine which assertions and source code statements are not consistent with the specification.

A scheduling approach to assembly sequence planning

This paper presents a model for the selection of optimal assembly sequences for a product in multirobot systems. The objective of the plan is the minimization of the total assembly time (makespan). To meet this objective, the model takes into account the assembly times and resources for each task, the times needed to change tools in the robots, and the delays due to the transportation of intermediate subassemblies between different workstations. The model can be used in different stages of the process planning. The paper includes two algorithmic approaches for solving the scheduling problem: a genetic algorithm intended for the earlier stages, and an A* algorithm for the final ones.

A MODEL FOR ASSEMBLY SEQUENCE PLANNING IN A MULTIROBOT ENVIRONMENT

Abstract This paper presents a model for the selection of optimal assembly sequences for a product in multirobot systems. The objective of the plan is the minimization of the total assembly time (makespan). To meet this objective, the model takes into account, in addition to the assembly times and resources for each task, the times needed to change tools in the robots, and the delays due to the transportation of intermediate subassemblies between different machines. An A* algorithm that solves the problem is also presented, which starts from the And/Or graph for the product (compressed representation of all feasible assembly plans).

Querying a polynomial object-relational constraint database in model-based diagnosis

Many papers related to Constraint Databases (CDBs) theories exist, including proposals that present frameworks for the treatment of constraints as a new data type. Our proposal presents a new way of storing and manipulating constraints as a usual data, and of making queries about the constraint variables derived from an Object-Relational Constraint Database (ORCDB). In this work, the constraints stored in an ORCDB are only polynomial equality constraints. The proposal is based on Grobner bases, constraint consistency and constraint optimisation techniques. Most works in CDB use spatial-temporal data as a case study, however this work presents an emergent engineering domain, that of fault diagnosis.

Improving the computational efficiency in symmetrical numeric constraint satisfaction problems

Models are used in science and engineering for experimentation, analysis, diagnosis or design. In some cases, they can be considered as numeric constraint satisfaction problems (NCSP). Many models are symmetrical NCSP. The consideration of symmetries ensures that NCSP-solver will find solutions if they exist on a smaller search space. Our work proposes a strategy to perform it. We transform the symmetrical NCSP into a new NCSP by means of addition of symmetry-breaking constraints before the search begins. The specification of a library of possible symmetries for numeric constraints allows an easy choice of these new constraints. The summarized results of the studied cases show the suitability of the symmetry-breaking constraints to improve the solving process of certain types of symmetrical NCSP. Their possible speed-up facilitates the application of modelling and solving larger and more realistic problems.

Generating multi-objective optimized configurable business process models

The manual specification of imperative business process (BP) models can be very complex and time-consuming, potentially leading to non-optimized models or even errors. To support process analysts in the definition of these models, a method for generating optimized configurable BP models from a constraint-based specification by considering multiple objectives is described. A constraint-based specification typically allows for several different ways of executing it leading to several enactment plans which can, however, vary greatly in respect to how well different performance objective functions can be achieved. We therefore automatically generate different plans and select the ones which fit best the objectives of the company. The generated plans are then merged into an optimized configurable BP model to support the model expert in choosing the most appropriate plan depending on the importance of each objective at configuration time.

A constraint-based model for multi-objective repair planning

This work presents a constraint based model for the planning and scheduling of disconnection and connection tasks when repairing faulty components in a system. Since multi-mode operations are considered, the problem involves the ordering and the selection of the tasks and modes from a set of alternatives, using the shared resources efficiently. Additionally, delays due to change of configurations and transportation are considered. The goal is the minimization of two objective functions: makespan and cost. The set of all feasible plans are represented by an extended And/Or graph, that embodies all of the constraints of the problem, allowing non reversible and parallel plans. A simple branch-and-bound algorithm has been used for testing the model with different combinations of the functions to minimize using the weighted-sum approach.

Automatic Generation of Questionnaires for Managing Configurable BP Models

Managing large collections of business process (BPs) models is increasingly being necessary for organizations. Configurable BP models can be used for managing these BPs while allowing analysts to understand what these BPs share and what their differences are. Before the execution of the configurable BP model, a BP model has to be selected from it. This selection is typically performed by an analyst who manually configures the model in order to address the business requirements. Unlike existing approaches, we propose a totally automated method to create a questionnaire-based application for guiding a business expert on configuring a model.

Improving the Determination of Minimal Hitting Sets in Model-Based Diagnosis Using Constraint Databases

: In model-based diagnosis, minimal hitting sets are usually used to identify which components may fail in a system. This work presents a set of algorithms to improve the determination of all Minimal Hitting Sets. Our proposal uses the minimal conflict sets to obtain, in an efficient way, the diagnosis of a system. The improvement consists of three algorithms which analyse only the relevant options. This proposal builds an equivalent system in order to obtain all minimal hitting sets depending on the location of the sensors. At the same time, all the information of the process is stored in a Constraint Database, keeping the information persistent and recoverable. Some empirical results are presented in order to show how the proposal improves the process in order to obtain all minimal hitting sets.