Production Line Layout Planning Based on Complexity Measurement

Mass customization production increases the difficulty of the production line layout planning. The material distribution process for variety of parts is very complex, which greatly increases the cost of material handling and logistics. In response to this problem, this paper presents an approach of production line layout planning based on complexity measurement. Firstly, by analyzing the influencing factors of equipment layout, the complexity model of production line is established by using information entropy theory. Then, the cost of the part logistics is derived considering different variety of parts. Furthermore, the function of optimization including two objectives of the lowest cost, and the least configuration complexity is built. Finally, the validity of the function is verified in a case study. The results show that the proposed approach may find the layout scheme with the lowest logistics cost and the least complexity. Optimized production line layout planning can effectively improve production efficiency and equipment utilization with lowest cost and complexity

On-line path planning by heuristic hierarchical search

In this paper, the problem of path planning for robot manipulators with six degrees of freedom in an on-line provided three-dimensional environment is investigated. As a basic approach, the best-first algorithm is used to search in the implicit descrete configuration space. Collisions are detected in the Cartesian workspace by hierarchical distance computation based on the given CAD model. The basic approach is extended by three simple mechanisms and results in a heuristic hierarchical search. This is done by adjusting the stepsize of the search to the distance between the robot and the obstacles. As a first step, we show encouraging experimental results with two degrees of freedom for five typical benchmark problems

Motion Planning for a Tethered Mobile Robot

Recently there has been surge of research in motion planning for tethered robots. In this problem a planar robot is connected via a cable of limited length to a fixed point in R2. The configuration space in this problem is more complicated than the one of a classic motion planning problem as existence of the cable causes additional constraints on the motion of the robot. In this thesis we are interested in finding a concise representation of the configuration space that results in a straightforward planning algorithm. To achieve such a representation we observe that configuration space manifold has a discrete structure that conveniently can be separated from its continuous aspect when it is represented as an atlas of charts. We provide a method for generating either the complete atlas or a subset of its charts based on special cable events. Generating parts of the configuration space on-the-fly enables the following improvements over the state-of-the-art. a) We decompose the environment into cells as needed rather than an off-line global discretization, obtaining competitive time and space complexity for our planner. b) We are able to exploit topological structure to represent robot-cable configurations concisely leading us towards solutions to the more complex problems of interest. To underscore the potential of this representation, we take further steps to generalize it to two more complicated instances of the tethered robot planning problem that has been widely disregarded in the literature. We will first consider a simplified model of cable-to-cable contacts, giving the robot the option to perform knot-like tying motions. Next, we will address the planning problem for a tethered robot whose cable has a constraint on its curvature. This adds to the realism of the model since most practical cables have some degree of stiffness which limits curvature. In this case we provide a novel technique to relate Dubins' theory of curves with work on planning with topological constraints. Our results show the efficiency of the method and indicate further promise for procedures that represent manifolds via an amalgamation of implicit discrete topological structure and explicit Euclidean cells

Grouping and Sequencing of Machining Operations for High Volume Transfer Lines

Transfer lines are employed for mass production of a fixed product or a very narrow range of product variants. This thesis considers a simple transfer line balancing problem with a focus on process planning and line configuration. Design features of the product are grouped and machining operations are sequenced in an optimal manner. The objective is to minimize the handling time fraction of the cycle time consisting mainly of orientation change time and tool change time. A new MILP model is developed to solve the problem with the aforementioned objectives while respecting a set of constraints, which include cutting tool allocation, tool magazine limit, tool life limit, takt time limit and precedence, inclusion & exclusion constraints. A problem-specific simulated annealing algorithm to solve large problems is also proposed. Numerical experiments are presented to illustrate the functionality of the MILP model and the meta-heuristic with respect to optimality and computation time

Analytical loading models and control strategies in flexible manufacturing systems: a comparative study

Ankara : Department of Industrial Engineering and the Institute of Engineering and Sciences of Bilkent University, 1990.Thesis (Master's) -- Bilkent University, 1990.Includes bibliographical references leaves 103-105There are three problem areas in designing and implementing a manufacturing line : the part family selection and grouping, system configuration and toolings and the operational control of manufacturing. The manufacturing process has to be stream-lined by considering resources and products to achieve flow lines operating around product families with acceptable levels of utilization. The stream-lined processes have to be assigned to tandem machines in the manufacturing lines. Then, interactions between production and inventory levels should be controlled at the operational level. Based on this framework, first a system configuration and tooling problem is modeled. The model turns out to be a large mLxed integer linear program, so that some alternative optimal seeking or heuristic techniques are used to solye the model for constructing a flow line structured Flexible Manufacturing System. Push systems of the Material Requirements Planning type or pull systems like the base-stock or Kanban schemes are often seen as alternatives for controlling manufacturing systems. The differentiating features of push, pull and a hybrid strategy are studied by discrete event simulation under different system and environmental characteristics for Flexible Manufacturing Systems. The impact of assignment of operations to machines on the performance of the system is also discussed.Kırkavak, NureddinM.S

Sampling-Based Temporal Logic Path Planning

In this paper, we propose a sampling-based motion planning algorithm that finds an infinite path satisfying a Linear Temporal Logic (LTL) formula over a set of properties satisfied by some regions in a given environment. The algorithm has three main features. First, it is incremental, in the sense that the procedure for finding a satisfying path at each iteration scales only with the number of new samples generated at that iteration. Second, the underlying graph is sparse, which guarantees the low complexity of the overall method. Third, it is probabilistically complete. Examples illustrating the usefulness and the performance of the method are included.Comment: 8 pages, 4 figures; extended version of the paper presented at IROS 201

Simulation-based optimization approach with scenario-based product sequence in a Reconfigurable Manufacturing System (RMS): A case study

In this study, we consider a production planning and resource allocation problem of a Reconfigurable Manufacturing System (RMS). Four general scenarios are considered for the product arrival sequence. The objective function aims to minimize total completion time of jobs. For a given set of input parameters defined by the market, we want to find the best configuration for the production line with respect to the number of resources and their allocation on workstations. In order to solve the problem, a hybridization approach based on simulation and optimization (Sim-Opt) is proposed. In the simulation phase, a Discrete Event Simulation (DES) model is developed. On the other hand, a simulated annealing (SA) algorithm is developed in Python to optimize the solution. In this approach, the results of the optimization feed the simulation model. On the other side, performance of these solutions are copied from simulation model to the optimization model. The best solution with the best performance can be achieved by this manually cyclic approach. The proposed approach is applied on a real case study from the automotive industry