Intelligent Manufacturing

Mass customization (MC) which was introduced by Davis (Future perfect, Addison-Wesley, Reading, MA 1987) has become a reality; nevertheless not all MC stories had a happy ending. Many companies implementing MC failed while some others succeeded such as National Bicycles Industrial Company of Japan, Hewlett-Packard, Motorola, Benetton, Chryslers, and Dell. How to determine the best MC strategy to be implemented or even if such a strategy should be adopted? In the literature many methods for implementing MC are found, however none of these propose a structured way for implementing and evaluating such a strategy as a whole, each concentrated on one department or phase of the supply or value chains. We suggest in this paper the use of extended value network modelling and simulation for evaluating an MC strategy, and we describe the modelling language used and the approach which will be applied into shoemaking industries via a European project named DOROTHY.

A solution to the problems of resource allocation and scheduling of loading and unloading operations in a container terminal is presented. The two problems are formulated and solved hierarchically. First, the solution of the resource allocation problem returns, over a number of work shifts, a set of quay cranes used to load and unload containers from the moored ships and the set of yard cranes to store those containers on the yard. Then, a scheduling problem is formulated to compute the loading and unloading lists of containers for each allocated crane. The feasibility of the solution is verified against a detailed, discrete-event based, simulation model of the terminal. The simulation results show that the optimized resource allocation, which reduces the costs by [frac13], can be effectively adopted in combination with the optimized loading and unloading list. Moreover, the simulation shows that the optimized lists reduce the number of crane conflicts on the yard and the average length of the truck queues in the terminal.

A complete knowledge based procedure for the design and manufacture of a round hole broach tool is described. The knowledge based design system (KBDS) produces a tool specification from user inputs describing the task to be performed. These design results are then used by the knowledge base to generate a geometric CAD/CAM representation, which can be utilized directly to display a drawing of the tool or to generate a CNC program for producing it. The process of formulating a knowledge-based design system demonstrates: the integration of expertise from experts, handbooks and theory; the awareness of restrictions on the scope of design that can be handled by a given system: the use of failure handling mechanisms to detect design failures and either adjust the emerging design or indicate infeasibility.

The US Army has launched an aggressive program to implement condition based maintenance on its rotary wing assets. Condition Based Maintenance takes advantage of technology developments in the areas of machinery monitoring, signal processing and fault modeling to reduce the cost of ownership through improved maintenance procedures. Documenting the reduction in maintenance burden, cost savings and increased safety through early detection of helicopter faults is an important step in justifying the program. This paper describes a novel technique used to detect a serious fault in the accessory section of the AH-64D Apache main transmission. The technique determines if the primary or secondary clutch system is driving the aircraft accessories through a tachometer speed ratio. The method has identified three aircraft operating on the secondary system allowing Army maintenance crews to replace the affected transmissions and quickly restore the aircraft to operational status.

... CR Boër (B) · L. Canetta · P. Pedrazzoli · C. Redaelli Institute CIM for Sustainable Innovation (ICIMSI), University of Applied Science of Southern Switzerland (SUPSI), Manno 6928, Switzerland e-mail: claudio.boer@supsi.ch L. Canetta e-mail: luca.canetta@supsi.ch P ...

Companies in either manufacturing or servicing have to be restructured or re-organized in order to overcome with challenges of the 21st century in which customers are not only satisfied but also delighted. In this competitive environment, organizations should use a flexible, adaptive and responsive paradigm that can be entitled by a unique term: agile manufacturing (AM). An AM system is able to develop a variety of product at low cost and in a short time period. For this, it has some of useful enabling technologies and physical tools. Among these, concurrent engineering (CE) is a systematic approach to the integrated, concurrent design of product and their related processes, including manufacture and support. It is then a useful and beneficial approach to reduce the development time and manufacturing cost, while simultaneously improving the quality of a product in order to better respond to the customer expectations. The aim of this study is to underline the synergistic impact of new product development (NPD) and CE, (which can be called CNPD), and to survey their methods and tools in association with the AM.

We study the problem of scheduling n jobs on two identical parallel processors or machines where an optimal schedule is defined as one with the shortest total weighted flowtime (i.e., the sum of the weighted completion time of all jobs), among the set of schedules with minimum makespan (i.e., the completion time of the last job finished). We present a two phase non-linear Integer Programming formulation for its solution, admittedly not to be practical or useful in most cases, but theoretically interesting since it models the problem. Thus, as an alternative, we propose an optimization algorithm, for small problems, and a heuristic, for large problems, to find optimal or near optimal solutions. Furthermore, we perform a computational study to evaluate and compare the effectiveness of the two proposed methods.

A heuristic-based optimization algorithm is proposed in this paper for on-line scheduling and assignment of preventive maintenance jobs to processors, to minimize under availability constraints, on a given time-window, the total cost of the maintenance operations of a distributed system. This algorithm minimizes the cost of discharge of preventive maintenance tasks or jobs, while assigning the tasks along with balancing the processors load. It is shown that the problem is NP-hard. To solve it, the concept of job emergency is introduced and the priority rule for total flow time (PRTF) criterion is used in an adapted heuristic job-scheduling model. In addition, the algorithm considers the constraints of precedence among consecutive standby jobs and their emergency. It is depicted the specific properties of the proposed heuristic allowing jobs scheduling in the right order. Computational results illustrate the efficiency of the approach implemented on different system configurations.

Inappropriate machining conditions such as cutting forces cause tool failures, poor surface quality and worst of all machine breakdowns. This may be avoided by using optimal machining parameters, e.g. feed-rate, and continuing to monitor it throughout the machining process. To optimize feed-rate, we propose a system that consists of an optimisation module, a process control module and a knowledge based evaluation module. STEP-NC is the underlying data model for optimisation. Given the nominal powers, the cutting force can be estimated based on the higher-level production information such as workpiece properties, tool materials and geometries, and machine capabilities. The main function of the Process Control module is process monitoring and control. The output is the desired actual feed-rate. Finally, the actual feed-rate is recorded and evaluated in the Knowledge Based Evaluation module.

This paper presents a tabu search approach for the job-shop scheduling problem. Although the problem is NP-hard, satisfactory solutions have been obtained recently by tabu search. However, tabu search has a problem-specific and parametric structure. Therefore, in the paper, we focussed on the tabu search strategies and parameters such as initial solution, neighborhood structure, tabu list, aspiration criterion, elite solutions list, intensification, diversification and the number of iteration. In order to compare some neighborhood strategies and tabu list length methods, a computational study is done on the benchmark problems.

Analysis and fuzzy control of an anthropomorphic robot arm on a special trajectory is the subject of this paper. These types of systems are used in cutting operations on materials, joining materials by welding, material handling in remote and dangerous environments, packing of foods, inspection/testing electronic parts or medical products. This robot arm realizes the handling motion on a special trajectory. In this study, the first three links of Mitsubishi RV-2AJ Industrial Robot, are like an anthropomorphic arm, have been modeled and simulated by using Dymola. Kinematic equations have been obtained and mathematical model of this system has been formed by using Lagrange’s Equations. Fuzzy logic controller for the joint angles for the motion trajectory has been designed and the simulation results have been presented at the end of the study.

Since the late 1970s when the first collection of papers on scheduling of flexible manufacturing systems (FMSs) has been published, it has been one of the most popular topics for researchers. A number of approaches have been delivered to schedule FMSs including simulation techniques and analytical methods, whereas the former is the most widely used tool for modeling FMSs. The objective of this paper is to review scheduling study on FMSs and analyse future trend that employed simulation techniques as the analyzing tool. Scheduling methodologies are categorized into, namely traditional simulation techniques with single criterion scheduling approaches, traditional simulation techniques with multi-criteria scheduling approaches, and artificial intelligence (AI) approaches in FMSs. It is concluded that AI approaches will be dominating in future study.