Cyclic scheduling of a 2-machine robotic cell with tooling constraints

In this study, we deal with the robotic cell scheduling problem with two machines and identical parts. In an ideal FMS, CNC machines are capable of performing all the required operations as long as the required tools are stored in their tool magazines. However, this assumption may be unrealistic at times since the tool magazines have limited capacity and in many practical instances the required number of tools exceeds this capacity. In this respect, our study assumes that some operations can only be processed on the first machine while some others can only be processed on the second machine due to tooling constraints. Remaining operations can be processed on either machine. The problem is to find the allocation of the remaining operations to the machines and the optimal robot move cycle that jointly minimize the cycle time. We prove that the optimal solution is either a 1-unit or a 2-unit robot move cycle and we present the regions of optimality. Finally, a sensitivity analysis on the results is conducted.     

Multi-level scheduling decisions in a class of FMS using simulation based metamodels

This paper pertains to a detailed simulation study conducted on a typical Flexible Manufacturing System (FMS). Initially, the configurations of the FMS under study have been established. Two types of FMSs have been evolved: one is failure free and the other is failure prone. For each of these cases, simulation models have been developed using SLAMSYSTEM. Orders arriving randomly at the FMS are subjected to three levels of scheduling decisions namely, launching of parts into the system, routing of parts through machines and sequencing of parts on AGVs at a central buffer. The simulation results have been used to develop metamodels for the two types of FMSs. These metamodels have been subjected to statistical analysis to ascertain their adequacy to represent the simulation models. These metamodels have been found to be useful for simulating the FMSs under study so as to evaluate various multi-level scheduling decisions in the FMS.     

A GPSS/H model for a hypothetical flexible manufacturing system

A GPSS/H model is presented for a hypothetical flexible manufacturing system. The FMS consists of six machines composed of three machine types, manufactures three types of parts, and uses automatic guided vehicles (AGVs) to transport inprocess parts between appropriate machines and wait spaces in the system. Three logical modules have been designed for the model, with copies of these modules then being appropriately distributed and interfaced throughout the model and tailored to achieve overall representation of the specific FMS. The same technique can be used by others to build analogous or extended GPSS/H models for other specific FMSs in which AGVs are used as transporters. Simulations can then be performed with such models to research FMS design and control alternatives.     

Representation and analysis of transfer lines with machines that have different processing rates

A transfer line is a tandem production system, i.e. a series of machines separated by buffers. Material flows from outside the system to the first machine, then to the first buffer, then to the second machine, the second buffer, and so forth. In some earlier models, buffers are finite, machines are unreliable, and the times that parts spend being processed at machines are equal at all machines. In this paper, a method is provided to extend a decomposition method to large systems in which machines are allowed to take different lengths of time performing operations on parts. Numerical and simulation results are provided.     

Optimal makespan schedule for three jobs on two machines

This paper deals with the problem of scheduling three jobs on two machines in order to minimize the makespan, when operation preemptions are forbidden and routes are fixed and may vary per job. It is shown that this problem can be solved by anO(r ⁴) algorithm, wherer is the maximal number of operations per job. Supported by Belarussian Fundamental Research Found, Project Φ60–242, and Deutsche Forschungsgemeinschaft, Project ScheMA     

Auxiliary tool allocation in flexible manufacturing systems

This paper analyses a new approach to the machine loading problem arising in flexible manufacturing systems (FMSs). This approach allows the operations to be assigned to machines assuming that machines have access to all the tools required for their operations. This exploits the flexibility of the FMS completely. Next an allocation of tools to machines is determined which satisfies the tool requirements for each machine and minimizes the total number of tools. Thus this approach minimizes the unnecessary tool duplications in the system and maximizes the tool utilization. The problem is modeled as an integer linear program (ILP). We notice that the main problem has a block diagonal structure which is decomposable by relaxing a set of linking constraints. Each separated sub-problem represents a problem of allocation of a single type of tools. We develop a branch-and-bound based exact solution procedure and three heuristic procedures to solve the sub-problems. Our lower bounding approach uses Lanrangean relaxation. The solutions to the Lagrangean relaxation are further used to determine the branching sequences and to develop heuristic approaches. Since finding even a feasible solution to the main problem is NP-hard, we develop only enumerative procedures to solve the main problem. Finally, these solution procedures are tested on randomly generated test problems.     

Modeling the interrelationship between downtimes and uptimes of CNC machines

Plant and equipment represent over 50% of the assets in most manufacturing industries. New technologies such as FMS are having a pervasive effect on technology adoption rates and the resultant productivity gains. The acquisition of CNC machines, which is an integral part of FMS, has been justified on financial grounds; however, this does not take the breakdown behavior of these machines into consideration. The downtime resulting from these breakdown leads to loss of productivity. In this paper an attempt has been made to determine the interrelationship between the downtimes and uptimes of CNC machines using transfer function modeling. The models are tested using data from a farm equipment manufacturer.     

Design,planning, scheduling,and control problems of flexible manufacturing systems

The design and use of flexible manufacturing systems (FMSs) involve some intricate operations research problems.FMS design problems include, for example, determining the appropriate number of machine tools of each type, the capacity of the material handling system, and the size of buffers.FMS planning problems include the determination of which parts should be simultaneously machined, the optimal partition of machine tools into groups, allocations of pallets and fixtures to part types, and the assignment of operations and associated cutting tools among the limited-capacity tool magazines of the machine tools.FMS scheduling problems include determining the optimal input sequence of parts and an optimal sequence at each machine tool given the current part mix.FMS control problems are those concerned with, for example, monitoring the system to be sure that requirements and due dates are being met and that unreliability problems are taken care of. This paper defines and describes these FMS problems in detail for OR/MS researchers to work on.     

On a disparity between relative cliquewidth and relative NLC-width

Cliquewidth and NLC-width are two closely related parameters that measure the complexity of graphs. Both clique- and NLC-width are defined to be the minimum number of labels required to create a labelled graph by certain terms of operations. Many hard problems on graphs become solvable in polynomial-time if the inputs are restricted to graphs of bounded clique- or NLC-width. Cliquewidth and NLC-width differ at most by a factor of two.The relative counterparts of these parameters are defined to be the minimum number of labels necessary to create a graph while the tree-structure of the term is fixed. We show that Relative Cliquewidth and Relative NLC-width differ significantly in computational complexity. While the former problem is NP-complete the latter is solvable in polynomial time. The relative NLC-width can be computed in O(n³) time, which also yields an exact algorithm for computing the NLC-width in time O(3ⁿn). Additionally, our technique enables a combinatorial characterisation of NLC-width that avoids the usual operations on labelled graphs.     

Scheduling unit — time tasks on flow — shops under resource constraints

We consider the problem of scheduling tasks on flow shops when each task may also require the use of additional resources. It is assumed that all operations have unit lengths, the resource requirements are of 0–1 type and there is one type of the additional resource in the system. It is proved that when the number of machines is arbitrary, the problem of minimizing schedule length is NP-hard, even when only one unit of the additional resource is available in the system. On the other hand, when the number of machines is fixed, then the problem is solvable in polynomial time, even for an arbitrary number of resource units available. For the two machine case anO(n log ₂ ² n) algorithm minimizing maximum lateness is also given. The presented results are also of importance in some message transmission systems.     

Customized sequential designs for random simulation experiments: Kriging metamodeling and bootstrapping

This paper proposes a novel method to select an experimental design for interpolation in random simulation, especially discrete event simulation. (Though the paper focuses on Kriging, this design approach may also apply to other types of metamodels such as non-linear regression models and splines.) Assuming that simulation requires much computer time, it is important to select a design with a small number of observations (or simulation runs). The proposed method is therefore sequential. Its novelty is that it accounts for the specific input/output behavior (or response function) of the particular simulation at hand; i.e., the method is customized or application-driven. A tool for this customization is bootstrapping, which enables the estimation of the variances of predictions for inputs not yet simulated. The method is tested through two classic simulation models, namely the expected steady-state waiting time of the M/M/1 queuing model, and the mean costs of a terminating (s, S) inventory simulation. For these two simulation models the novel design indeed gives better results than a popular alternative design, namely Latin Hypercube Sampling (LHS) with a prefixed sample.     

Algorithms for part and machine selection in flexible manufacturing systems

Deciding whether FMS technology is viable for a given application, and if so, what machines should comprise the FMS and what parts should be produced on it, can be a difficult task. Manual methods suffice only for situations where a small number of FMS-type machines are to be considered and less than a few dozen candidate parts are to be chosen from. When both machines and parts are to be selected from a larger number of candidates, manual methods become cumbersome and time consuming, and computer-based decision aids become a necessity. This paper gives an overview of the required decision process, and then focuses on those stages for which computer-based decision aids can be used effectively. Particular decision aids are described, and case studies are cited to illustrate their motivation and use.     

A production planning problem in FMS

We present in this work a hierarchical approach for generating alternatives for production planning in a generic floor shop problem within the environment of Flexible Manufacturing Systems (hereafter, FMS). Briefly, the problem can be stated as follows: Given the resources of a FMS and the characteristics of the parts to be produced along a planning horizon, obtain the loading ordering of the parts in the FMS, the execution ordering of the operations and the processing route of each part (i.e., the working stations where each operation is to be executed), such that the production and transport costs are minimized and the modules workload is levelized. The problem is decomposed into three subproblems which are arranged in a hierarchy; a variety of models is presented, as well as the input/output relations that allow to integrate them; we also propose some algorithmic ideas to exploit the special structure of the problem. Computational experience is reported.     

A polynomial algorithm for a two-machine no-wait job-shop scheduling problem

This paper considers the no-wait scheduling of n jobs, where each job is a chain of unit processing time operations to be processed alternately on two machines. The objective is to minimize the mean flow time. We propose an O(n⁶)-time algorithm to produce an optimal schedule. It is also shown that if zero processing time operations are allowed, then the problem is NP-hard in the strong sense.     

Batching and routing: Two functions in the operational planning of flexible manufacturing systems

The success of a Flexible Manufacturing System (FMS) is based on many factors such as the appropriate selection of parts, machine tools and material handling systems, effective planning and a full specification of the control software. In particular, planning must be carried out effectively at many different levels. The production operations of FMS's are planned at one of these levels, and this paper presents a new functional structure for this planning task, called operational planning. Four operational planning functions are identified: batching, routing, dispatching and sequencing. The models that are used to represent the batching and routing problems are presented in detail. The models are formulated as mixed integer programming models, which broadly specify the capacity constraints of the FMS, enabling the decision-maker to look for planning alternatives in a variable time horizon. Results are derived using data from an existing FMS.     

Contribution of simulation to the optimization of maintenance strategies for a randomly failing production system

This paper compares two strategies for operating a production system composed of two machines working in parallel and a downstream inventory supplying an assembly line. The two machines, which are prone to random failures, undergo preventive and corrective maintenance operations. These operations with a random duration make the machines unavailable. Moreover, during regular subcontracting operations, one of these machines becomes unavailable to supply the downstream inventory. In the first strategy it is assumed that the periodicity of preventive maintenance operations and the production rate of each machine are independent. The second strategy suggests an interaction between the periods of unavailability and the production rates of the two machines in order to minimize production losses during these periods. A simulation model for each strategy is developed so as to be able to compare them and to simultaneously determine the timing of preventive maintenance on each machine considering the total average cost per time unit as the performance criterion. The second strategy is then considered, and a multi-criteria analysis is adopted to reach the best cost-availability compromise.     

Continue,quit, restart probability model

We discuss a new applied probability model: there is a system whose evolution is described by a Markov chain (MC) with known transition matrix on a discrete state space and at each moment of a discrete time a decision maker can apply one of three possible actions: continue, quit, and restart MC in one of a finite number of fixed “restarting” points. Such a model is a generalization of a model due to Katehakis and Veinott (Math. Oper. Res. 12:262, 1987), where a restart to a unique point was allowed without any fee and quit action was absent. Both models are related to Gittins index and to another index defined in a Whittle family of stopping retirement problems. We propose a transparent recursive finite algorithm to solve our model by performing O(n³) operations.     

Approximate analysis of unreliable transfer lines with splits in the flow of material

This paper presents a Markov process model and an approximate decomposition technique for a discrete material transfer line with limited buffer capacity. A fraction of the parts processed at some stations in the line may be scrapped or reworked at dedicated machines to meet product quality requirements. Reworked parts are not sent back into the main line. This leads to splits in the flow of material. Processing times are deterministic and identical for all machines and are taken as the time unit. Machine specific times to failure and to repair are geometrically distributed. The model is analyzed through a decomposition into twomachine systems. We develop new decomposition equations for machines performing split operations. Production rates and inventory levels are computed and compared to simulation results. The results indicate that the method produces useful results for a variety of systems.     

The basic theory of infinite time register machines

Infinite time register machines (ITRMs) are register machines which act on natural numbers and which are allowed to run for arbitrarily many ordinal steps. Successor steps are determined by standard register machine commands. At limit times register contents are defined by appropriate limit operations. In this paper, we examine the ITRMs introduced by the third and fourth author (Koepke and Miller in Logic and Theory of Algorithms LNCS, pp. 306–315, 2008), where a register content at a limit time is set to the lim inf of previous register contents if that limit is finite; otherwise the register is reset to 0. The theory of these machines has several similarities to the infinite time Turing machines (ITTMs) of Hamkins and Lewis. The machines can decide all ${\Pi^1_1}Infinite time register machines (ITRMs) are register machines which act on natural numbers and which are allowed to run for arbitrarily many ordinal steps. Successor steps are determined by standard register machine commands. At limit times register contents are defined by appropriate limit operations. In this paper, we examine the ITRMs introduced by the third and fourth author (Koepke and Miller in Logic and Theory of Algorithms LNCS, pp. 306–315, 2008), where a register content at a limit time is set to the lim inf of previous register contents if that limit is finite; otherwise the register is reset to 0. The theory of these machines has several similarities to the infinite time Turing machines (ITTMs) of Hamkins and Lewis. The machines can decide all P¹₁{\Pi^1_1} sets, yet are strictly weaker than ITTMs. As in the ITTM situation, we introduce a notion of ITRM-clockable ordinals corresponding to the running times of computations. These form a transitive initial segment of the ordinals. Furthermore we prove a Lost Melody theorem: there is a real r such that there is a program P that halts on the empty input for all oracle contents and outputs 1 iff the oracle number is r, but no program can decide for every natural number n whether or not n ? r{n \in r} with the empty oracle. In an earlier paper, the third author considered another type of machines where registers were not reset at infinite lim inf’s and he called them infinite time register machines. Because the resetting machines correspond much better to ITTMs we hold that in future the resetting register machines should be called ITRMs.