Object-oriented and distributed approach for programming robotic manufacturing cells

Flexible manufacturing systems (FMS) are essential for small/medium batch and job shop manufacturing. These types of production systems are used to manufacture a considerable variety of products with medium/small production volumes. Therefore, the manufacturing platforms supporting these types of production must be flexible and organized in flexible manufacturing cells (FMC). Programming FMCs remains a difficult task and is an actual area of research and development. This paper reports an object-oriented approach developed for FMC programming. The work presented was first thought for application in industrial robot manipulators, and later extended to other FMC equipments just by putting the underlying ideas in a general framework. Initially, the motivation for this work was to develop means to add force control to a standard industrial robot manipulator. This problem requires remote access to the robot controller, remote programming and monitoring, as also is required to program and monitor any other FMC equipment. The proposed approach is distributed based on a client/server model and runs on Win32 platforms, i.e., Microsoft Windows and Windows NT. Implementation for the special case of industrial robot manipulators is presented, along with some application examples used for educational, research and industrial purposes.     

Ant colony optimization approach to a fuzzy goal programming model for a machine tool selection and operation allocation problem in an FMS

Due to the global competition in manufacturing environment, firms are forced to consider increasing the quality and responsiveness to customization, while decreasing costs. The evolution of flexible manufacturing systems (FMSs) offers great potential for increasing flexibility and changing the basis of competition by ensuring both cost effective and customized manufacturing at the same time. Some of the important planning problems that need realistic modelling and quicker solution especially in automated manufacturing systems have assumed greater significance in the recent past. The language used by the industrial workers is fuzzy in nature, which results in failure of the models considering deterministic situations. The situation in the real life shop floor demands to adopt fuzzy-based multi-objective goals to express the target set by the management. This paper presents a fuzzy goal programming approach to model the machine tool selection and operation allocation problem of FMS. An ant colony optimization (ACO)-based approach is applied to optimize the model and the results of the computational experiments are reported.     

Visual C++环境下的汇编语言与高级语言混合编程

本文讨论了Win32环境下应用程序的一般机制与特点,论述了基于Windows操作系统和x86指令集的汇编语言程序设计方法,分析了依赖于Visual C 开发环境的函数调用约定.通过对比C 和汇编程序,给出一个混合编程的实例,结果说明了两种语言函数之间的等价性.     

An embedded implementation of the Common Language Infrastructure

The Common Language Infrastructure provides a unified instruction set which may be targeted by a variety of high level language compilers. This unified instruction set simplifies the construction of compilers and gives application designers the ability to choose the high level programming language that best suits the problem being solved. While the Common Language Infrastructure solves many problems related to design of applications and compilers, it is not without its own problems. The Common Language Infrastructure is based upon a virtual machine, much like the Java Virtual Machine. This requires that all instructions being executed on the Common Language Infrastructure be translated to native machine instructions before they can be executed on the host processor. This leads to degradation in performance. In order to overcome this problem it is proposed that an embedded processor capable of natively executing the CLI instruction set be developed. The objective of this work is the design and implementation, using VHDL and simulation, of an embedded processor capable of natively executing the CLI instruction set. This processor provides a platform easily targeted by software developers.     

Optimization of machining processes from the perspective of energy consumption: A case study

One of the primary objectives of sustainable manufacturing is to minimize energy consumption in its manufacturing processes. A strategy of energy saving is to adapt new materials or new processes; but its implementation requires radical changes of the manufacturing system and usually a heavy initial investment. The other strategy is to optimize existing manufacturing processes from the perspective of energy saving. However, an explicit relational model between machining parameters and energy cost is required; while most of the works in this field treat the manufacturing processes as black or gray boxes. In this paper, analytical energy modeling for the explicit relations of machining parameters and energy consumption is investigated, and the modeling method is based on the kinematic and dynamic behaviors of chosen machine tools. The developed model is applied to optimize the machine setup for energy saving. A new parallel kinematic machine Exechon is used to demonstrate the procedure of energy modeling. The simulation results indicate that the optimization can result in 67% energy saving for the specific drilling operation of the given machine tool. This approach can be extended and applied to other machines to establish their energy models for sustainable manufacturing.     

Capacity utilization and machine sharing in a group technology based manufacturing system

Each cell in a group technology-based manufacturing system can be assumed as being comprised of two categories of machine types: (a) Dedicated to the cell, (b) Shared by other cells. The shared machine types constitute the major problem in the implementation of a cellular manufacturing system. This paper demonstrates, using a hypothetical case study, a mathematical programming formulation that exploits the existence of shared machine types in a cellular manufacturing system. Part transfer for the parts whose output levels are restricted by available capacity or shared machine types can be found which will minimize the material handling penalties.     

Designing cellular manufacturing systems under dynamic and uncertain conditions

The paper proposes a fuzzy programming based approach to design a cellular manufacturing system under dynamic and uncertain conditions. The dynamic condition indicates a multi-period planning horizon, in which the product mix and demand in each period can be different. As a result, the best cells designed for one period may not be efficient cells for subsequent periods and some of reconfigurations are required. Uncertain condition implicates to the imprecise nature of the part demand and also the availability of the manufacturing facilities in each period planning. An extended mixed-integer programming model of dynamic cellular manufacturing system, in which some of the coefficients in objective function and constraints are fuzzy quantities, is solved by a developed fuzzy programming based approach. The objective is to determine the optimal cell configuration in each period with maximum satisfaction degree of the fuzzy objective and constraint. To illustrate the behavior of the proposed model and verify the performance of the developed approach, a number of numerical examples are solved and the associated computational results are reported.     

Decision-making method of reconfigurable manufacturing systems’ reconfiguration by a Gale-Shapley model

The companies need to rapid response to new product introduction, mix and demand changes to stay competitive. A reconfigurable manufacturing system can quickly react to changes in products and market. The control method to reconfigure the machines of a reconfigurable manufacturing system is crucial for the performance level. This paper proposes a reconfiguration decision-making method based on a Game-Theory algorithm, and in particular the Gale-Shapley model. A periodic review strategy is used to create two sets: one set of machine over-loaded and one set under-loaded. The Gale-Shapley model forms a coupled of over-loaded and under-loaded machines. The reconfiguration concerns the under-loaded machine of the coupled adding also the task performed by the over-loaded machine. This paper presents a simulation environment developed to evaluate the proposed method and highlight the main topics. The simulation results highlight how the game-theory approach developed improves all the performance measures with controlled number of machines’ reconfigurations.     

Self-organizing migration algorithm applied to machining allocation of clutch assembly

Tolerancing is an important issue in product and manufacturing process designs. The allocation of design tolerances between the components of a mechanical assembly and manufacturing tolerances in the intermediate machining steps of component fabrication can significantly affect the quality, robustness and life-cycle of a product. Stimulated by the growing demand for improving the reliability and performance of manufacturing process designs, the tolerance design optimization has been receiving significant attention from researchers in the field. In recent years, a broad class of meta-heuristics algorithms has been developed for tolerance optimization. Recently, a new class of stochastic optimization algorithm called self-organizing migrating algorithm (SOMA) was proposed in literature. SOMA works on a population of potential solutions called specimen and it is based on the self-organizing behavior of groups of individuals in a “social environment”. This paper introduces a modified SOMA approach based on Gaussian operator (GSOMA) to solve the machining tolerance allocation of an overrunning clutch assembly. The objective is to obtain optimum tolerances of the individual components for the minimum cost of manufacturing. Simulation results obtained by the SOMA and GSOMA approaches are compared with results presented in recent literature using geometric programming, genetic algorithm, and particle swarm optimization.     

Minimization of squared deviation of completion times about a common due date

We discuss a non-preemptive single-machine job sequencing problem where the objective is to minimize the sum of squared deviation of completion times of jobs from a common due date. There are three versions of the problem—tightly restricted, restricted and unrestricted. Separate dynamic programming formulations have already been suggested for each of these versions, but no unified approach is available. We have proposed a pseudo-polynomial DP solution and a polynomial heuristic for general instance. Computational results show that tightly restricted instances of up to 600 jobs can be solved in less than 6 s. General instances of up to 80 jobs take less than 2 s.Statement of scope and purposeIn this paper, we have considered an NP-complete single-machine scheduling problem arising in JIT environment, a field of great importance in manufacturing industry. The objective of the problem is to schedule a set of given jobs to minimize the sum of squared deviation of their completion times from a common due date. This paper presents a number of precedence rules, a polynomial heuristic and more importantly a unified pseudo-polynomial dynamic programming formulation. Empirical results show that the dynamic programming formulation performs better than the existing approaches.     

A simple way to construct interactive processors

A FORTRAN program is presented which reads instruction lines entered from a timesharing terminal, and interprets them as beginning with an instruction word and continuing with “declarations”. The instruction word and the information in the declarations are passed to a linking subroutine and thence to a set of user-supplied subroutines which act on the instruction. The program is in effect the nucleus of a processor and, when linked to a working set of subroutines, it can be made to approximate to a simple computer “language”. Any number of such languages can be built with the program as a basis. A language of this sort is unlikely to be as powerful, as versatile, or as generalized as FORTRAN, but it is certain to be simpler to work with in the user's particular context, to which it can be adjusted as nicely as programming time and costs permit. The program is not very useful for small or circumscribed tasks, or for applications already covered by standard libraries; its value lies rather in simplifying specialized tasks of moderate complexity and diversity. A companion paper illustrates a use of the program in a processor for handling data obtained with a digitizer.     

Solving a multi-floor layout design model of a dynamic cellular manufacturing system by an efficient genetic algorithm

This paper presents a mixed-integer programming model for a multi-floor layout design of cellular manufacturing systems (CMSs) in a dynamic environment. A novel aspect of this model is to concurrently determine the cell formation (CF) and group layout (GL) as the interrelated decisions involved in the design of a CMS in order to achieve an optimal (or near-optimal) design solution for a multi-floor factory in a multi-period planning horizon. Other design aspects are to design a multi-floor layout to form cells in different floors, a multi-rows layout of equal area facilities in each cell, flexible reconfigurations of cells during successive periods, distance-based material handling cost, and machine depot keeping idle machines. This model incorporates with an extensive coverage of important manufacturing features used in the design of CMSs. The objective is to minimize the total costs of intra-cell, inter-cell, and inter-floor material handling, purchasing machines, machine processing, machine overhead, and machine relocation. Two numerical examples are solved by the CPLEX software to verify the performance of the presented model and illustrate the model features. Since this model belongs to NP-hard class, an efficient genetic algorithm (GA) with a matrix-based chromosome structure is proposed to derive near-optimal solutions. To verify its computational efficiency in comparison to the CPLEX software, several test problems with different sizes and settings are implemented. The efficiency of the proposed GA in terms of the objective function value and computational time is proved by the obtained results.     

Criteria for selecting control systems in flexible manufacturing

Industry in Europe has been undergoing major structural changes during the last twenty years or so. Against the background of high demand for consumer and capital goods with corresponding, mostly fixed production capacities, it was necessary to build flexible and, at the same time, efficient production plants in order to cope with the increasing variety of products and shorter innovation cycles.Flexible manufacturing is inconceivable without information technology. Thus, the word “information” has rightly taken its place in the list of primary factors associated with modern production technology. The “gating” of data into production planning and quality assurance, combined with concepts of logistics and control, keeps the flow of materials on the move and helps to shorten lead times.The organization of production and the plant equipment itself have to be matched to the size of the plant, the product range and the market. In large-batch production, for example, a customized vehicle is required; in small-batch or unit production it is often necessary to manufacture a machine to specific customer requirements. Despite such great variations in the type of requirement, it is still possible to distinguish a number of common factors—one of them being the hierarchical structure of the automation landscape with objective and transparent distribution of information across all levels; from the control level for pre-production, assembly and transport up to the planning level for capacity planning and materials management.Hierarchical levels enable particular tasks to be assigned to specific automation equipment. Mainframes and minicomputers are used at the planning level. Dedicated systems such as numerical controls and programmable controllers are now used almost exclusively on the shopfloor control level.Local area networks connect the automation systems of different manufactures without the need for any adaptation. Protocols must be unified for this purpose. Since stable standards are not yet in existence, Siemens has decided to follow the strategy of standard harmonized development.Programmable controllers are part of all production, transport and storage systems. The main requirements are for control, operator communication, monitoring, counting and positioning. A comprehensive production family is a very important factor. Excellent hardware compatibility, easy interlinking and a uniform programming language are all characteristic of the family philosophy.Industrial robots are used mainly in the automobile industry. Largely thaks to them it is possible to produce economically and rationally any mix of model variants and to automate assembly. Programming facilities such as teach-in, on-line or off-line are therefore an important selection criterion for robot control.The majority of numerical controls in use today are used for controlling single machines in heavy-duty and special-purpose machinery manufacture. In networked applications, numerical controls form part of flexible manufacturing systems. In addition to machine control and management, the capacity for communication is an important criterion for selection in this case.In many controls for individual machines the priority is for quick and easy programming. “Shopfloor programming” has assumed considerable importance in such applications. Shopfloor programming requires controls with a sophisticated, user-friendly, graphics interface.Examples show how dedicated automation subsystems have been finding widespread application in the automation of manufacturing, transport and warehouse equipment. They are designed specially to perform certain tasks, both in programming and operation, in order to provide an economic solution to a problems in terms of matched performance and functionality.     

Value function-based approach to the scheduling of multiple controllers

Both gain scheduling and multiple model based control approaches are considered to be practical approaches for control of industrial nonlinear processes. However, the former ignores system dynamics and the latter is specific to the type of controller design and limited in its scope of application as practiced in industry. This paper proposes a value function-based strategy for switching among local controllers, thereby providing an effective global control policy for the entire operating regions. The suggested method selects the best one among a set of available control policies at each time step by evaluating the “value” function associated with the successive state when a particular control action instructed by a candidate policy is taken for a give state. The value function, which maps a state to its associated discounted infinite horizon cost-to-go, is obtained by solving the dynamic programming in an approximate way using closed-loop simulation or operational data and a function approximator. The proposed approach has the advantages that candidate controllers are general and the switching is performed not by a fixed heuristic rule but rigorously via dynamic programming. From the viewpoint of dynamic programming, the approach helps alleviate the curse of dimensionality with respect to the state space and action space. Optimal or approximately optimal switching rules can be learned without a model, which defines the state transitional rule. The approach is demonstrated on several different nonlinear control examples.     

Predictive pull-based control of an unmanned manufacturing cell, accounting for robot mobility

In order to remove the cell size limitation and to make cellular manufacturing systems more flexible, a manufacturing cell has been equipped with a mobile robot which moves from machine to machine, much like its human counterpart would do. To further acquire a portion of the attributes (intelligence and adaptability of the human worker) lost in robotizing the traditional manned manufacturing cell, a “limited” knowledge-based cell control algorithm is developed. This algorithm maintains standard pull control logic as its underlying basis while utilizing heuristically, knowledge of the ongoing processes and their current status. In this paper, an analysis of this ‘new’ predictive pull-based controller is presented. The simulation results from the predictive pull-based controller are evaluated and compared with the standard pull control logic, first come first serve and shortest distance. A test-bed of an unmanned manufacturing cell with a self-propelled mobile robot was used for experimental verification. Simulation and experimental results show that the degree of improvements gained in the cell performance over the standard pull control method is dependent on the robot’s mobility velocity and how much part inspection/part rejection is performed within the cell. In conclusion, the predictive pull-based algorithm is relatively simple variation of pull control which has the ability of enhancing the “near optimal” pull cell control performance.     

AGAPIA v0.1: A Programming Language for Interactive Systems and Its Typing System

A model (consisting of rv-systems), a core programming language (for developing rv-programs), several specification and analysis techniques appropriate for modeling, programming and reasoning about interactive computing systems have been recently introduced by Stefanescu using register machines and space-time duality, see [Stefanescu, G. Interactive systems with registers and voices. Fundamenta Informaticae 73 (2006), 285–306. (Early draft, School of Computing, National University of Singapore, July 2004.)]. After that, Dragoi and Stefanescu have developed structured programming techniques for rv-systems and their verification, see, e.g., [Dragoi, C., and G. Stefanescu. Structured programming for interactive rv-systems. Institute of Mathematics of the Romanian Academy, IMAR Preprint 9/2006, Bucharest 2006. Dragoi, C., and G. Stefanescu. Towards a Hoare-like logic for structured rv-programs. Institute of Mathematics of the Romanian Academy, IMAR Preprint 10/2006, Bucharest, 2006. Dragoi, C., and G. Stefanescu. Implementation and verification of ring termination detection protocols using structured rv-programs. Annals of University of Bucharest, Mathematics-Informatics Series, 55 (2006), 129–138. Dragoi, C., and G. Stefanescu. Structured interactive programs with registers and voices and their verification. Draft, Bucharest, January 2007. Dragoi, C., and G. Stefanescu. On compiling structured interactive programs with registers and voices. In: “Proc. SOFSEM 2008,” 259–270. LNCS 4910, Springer, 2008.].In the present paper a kernel programming language AGAPIA v0.1 for interactive systems is introduced. The language contains definitions for complex spatial and temporal data, arithmetic and boolean expressions, modules, and while-programming statements with their temporal, spatial, and spatio-temporal versions. In AGAPIA v0.1 one can write programs for open processes located at various sites and having their temporal windows of adequate reaction to the environment. The main technical part of the paper describes a typing system for AGAPIA v0.1 programs.     

Synchronous/Reactive Programming of Concurrent System Software

Synchronous languages are intended for programming reactive systems. Reactive systems, which include real-time systems and key operating system components, interact continually with their environment. This paper considers the applicability of imperative synchronous/reactive languages to the development of general system software, that is, to the implementation of operating system kernels, file systems, databases, networks, server architectures, device drivers, etc. The languages Esterel and Reactive C (RC) receive special attention as Esterel is the oldest and most developed such language and RC is specifically designed for compatibility with C systems programming. An alternative soft-instruction software architecture is described, which is well suited to real-world system programming. © 1997 by John Wiley & Sons, Ltd.     

A constraint programming approach to tool allocation and production scheduling in flexible manufacturing systems

This paper presents a constraint programming (CP) methodology to deal with the scheduling of flexible manufacturing systems (FMSs). The proposed approach, which consists of both a model and a search strategy, handles several features found in industrial environments, such as limitations on number of tools in the system, lifetime of tools, as well as tool magazine capacity of machines. In addition, it tackles the problem in a integrated way by considering tool planning and allocation, machine assignment, part routing, and task timing decisions altogether in the approach. The formulation, which is able to take into account a variety of objective functions, has been successfully applied to the solution of test problems of various sizes and degrees of difficulty.     

Duality theory in fuzzy mathematical programming problems with fuzzy coefficients

In this paper, the notions of subgradient, subdifferential, and differential with respect to convex fuzzy mappings are investigated, which provides the basis for the fuzzy extremum problem theory. We consider the problems of minimizing or maximizing a convex fuzzy mapping over a convex set and develop the necessary and/or sufficient optimality conditions. Furthermore, the concept of saddle-points and minimax theorems under fuzzy environment is discussed. The results obtained are used to formulate the Lagrangian dual of fuzzy programming. Under certain fuzzy convexity assumptions, KKT conditions for fuzzy programming are derived, and the “perturbed” convex fuzzy programming is considered. Finally, these results are applied to fuzzy linear programming and fuzzy quadratic programming.     

MCLP-based methods for improving “Bad” catching rate in credit cardholder behavior analysis

Cardholders’ behavior prediction is an important issue in credit card portfolio management. As a promising data mining approach, multiple criteria programming (MCLP) has been successfully applied to classify credit cardholders’ behavior into two groups. In order to better control credit risk for financial institutes, this paper proposes three methods based on MCLP to improve the “Bad” catching accuracy rate. One is called MCLP with unbalanced training set selection, the second is called fuzzy linear programming (FLP) method with moving boundary, and the third is called penalized multi criteria linear programming (PMCLP). The experimental examples demonstrate the promising performance of these methods.