Soheil Khajenoori

Using system reliability to determine supportability turnaround time at a repair depot

This paper uses an expression for system reliability at a repair depot to construct a nonlinear, nonpolynomial function which is amenable to numerical analysis and has a zero equal to the supportability turnaround time (STAT) for a failed unit. System reliability is in terms of the constant failure rate for all units, number of spares on-hand at the time a unit fails, and projected repair completion dates for up to four unrepaired units. In this context, STAT represents the longest repair time (for a failed unit) which assures a given reliability level; system reliability is the probability that spares are ready to replace failed units during the STAT period. The ability to calculate STAT-values is important for two reasons: (1) subtraction of the repair time for a failed unit from its STAT-value yields the latest repair start-time (for this unit) which assures a desired reliability, and (2) the earlier the latest repair start-time, the higher the priority for starting the repair of this unit. Theorems show the location of STAT with respect to the list of repair completion dates, and form the foundation of the root-finding-based algorithm for computing STAT-values. Numerical examples illustrate the algorithm.

Smart scheduling for better repair-depot reliability

Linton et al. (1995) use an expression for the reliability of the system for repairing failed units (FU) at a repair depot to compute the longest repair time for a newly failed unit (NFU) which assures a given reliability level (also termed the NFU supportability turnaround time or STAT) in terms of the constant failure rate for all components, the number of spares on-hand, and projected downstream repair completion times for FU. Since subtraction of the repair time for a NFU from its STAT-value yields the NFUs latest repair start-time (RST) which assures a given repair-depot system reliability (RD-SR), STAT-values are important for scheduling RST. If a NFUs latest RST is negative, however, the NFU cannot be repaired and returned to the status of a spare in time to assure the desired RD-SR level. When a NFUs latest RST is negative and some previously FU have not yet begun their repair, then Sched-Alg (the algorithm in this paper)-(i) shows whether or not it is possible to reschedule RST for FU so that the latest RST for the NFU is nonnegative (and, hence, the desired RD-SR can be maintained) and, if a reassignment of RST to meet RD-SR is possible; and (ii) determines a new RST schedule for FU which ensures the desired RD-SR, minimizes the number of adjustments required, and reduces the total adjustment time. Numerical examples illustrate Sched-Alg.

STARSIM: an object-oriented simulation model of Space Shuttle ground processing activities

STARSIM (Space Transportation Activities and Resources SIMulation) is an object-oriented, menu-driven, user-friendly, decision support system for simulating and managing Space-Shuttle ground processing activities. The purpose of STARSIM is to permit trade-off studies to be performed for any set of input parameters (e.g., determining the effects on launches per year of adding a bay in the orbiter processing facility). Output is displayed both numerically (for global statistical information, including life-cycle cost estimates) and in Gantt chart form (for visualizing when and where each orbiter vehicle experiences waiting, processing, blocking and maintenance periods, as well as the reasons for blocking).<<ETX>>

A fast algorithm for repair-depot reliability-evaluation

The repair-depot (where failed items are replaced with spares and scheduled for repair) system-reliability (RDSR) is the probability that spares are immediately available to replace failed units during the time period of interest, and it is calculated in terms of the constant failure rate for parts under consideration, the number of spare units on-hand (s), and projected repair completion dates for (n-1) units in the repair process, n/spl ges/2. Linton et al. (1995) show an expression for RDSR in terms of n nested sums, where the upper limit of each sum is a function of s. This paper derives a restructured expression (LKYH algorithm) for computing RDSR, and shows that the nested-sum form for RDSR uses O(s/sup n/) mathematical operations, while LKYH requires only O(s) mathematical operations. Numerical examples illustrate the increase in efficiency of LKYH; e.g., when n=s=10, the execution time for computing RDSR on a 486/66-computer is reduced from 198 seconds for the multiple-sum form to less than 1 second for LKYH.

A graphics engine for design of three-dimensional structures from standardized component modules

Abstract We present an interactive, menu-driven software package which allows the design of three-dimensional structures from standardized component modules. The standardized component modules used as example building blocks in the project are rectangular solids of several sizes. The system has been designed such that its output (i.e. the design database) can be used to automatically generate a robot motion program to assemble the designed structure. Presented are the system database and its internal data structure, an object placement-sequencer algorithm, a height specification and interference checking algorithm, and a balance-checking algorithm. To avoid the creation of dynamic obstacles and interference of the robot arm with these obstacles, the proper sequencing of the blocks in the design database is essential. The object placement-sequencer algorithm is responsible for proper sequencing of the blocks in the design database to avoid the aforementioned problem. The height specification and interference checking algorithm automatically generates the proper positioning of a block in the design by performing a sequential search over the accumulated design structure. The stacking feasibility of the blocks in the design is verified by the balance-checking algorithm, prior to the acceptance of the block as a permanent part of the design.

Reporter Object: An Analysis Module Which Aids in Verifying, Validating and Graphically Displaying Results of Simulation Models

In order to verify, validate and graphically display results for simulation models, an analysis module (separate from the simulation itself) called Reporter Object (RO) was developed. RO receives log files (in a particular format) from any simulation model and produces (a) Gantt-type charts, showing all waiting, processing, and blocking times (including reasons for the blocking) for all desired objects (or entities) at all processing facility locations at all times of interest, and (b) pie charts depicting the percen tages represen ted by subcategories associated with a main category (e.g., the percentages of direct material, direct labor and indirect fixed costs associated with total cost). RO was designed to be either integrated with an object-oriented simulation engine or executed as a separate program for use with any simulation model. In order to illustrate its capabilities, Reporter Object is used in conjunction with STARSIM (an acronym for Space Transportation Activities and Resources SIMulation), an object- oriented, menu-driven, simulation model of Space-Shuttleground processing activities, to show ROs architectural relationship to the simulation engine, the format of required log files (and potential extensions), the types of output that may be produced and the ramifications of this output.

An expert system for paperwork optimization in production systems

Abstract Much like material handling, process paperwork only contributes to overhead cost (not proportionally included in the final product). The very computing technologies that have produced electronic mail systems (and similar paper-less information systems) have also made it quite easy and tempting to generate excessive paperwork in form of memos, reports, charts, lists, files, etc. This paper describes an expert system for minimizing such paperwork activities in various production systems.

A procedure for selecting optimal set of processors under time constraints

A decomposition heuristic is presented for the problem of selecting a minimum-cost set of processors that can complete a given set of tasks within a given period of time. This problem, which belongs to the NP-complete class of optimization problems, is encountered in designing manufacturing systems consisting mainly of robots and other programmable manipulators. There are two parts to the heuristic. The main part is a decomposition procedure that goes back and forth between two subproblems, one a transportation problem and the other a critical-path problem. The other part is a special set-covering procedure. Computational results are reported.<<ETX>>

Computing the productivity of multistation serial manufacturing systems: a heuristics approach

Abstract Analytical models to evaluate the performance of multistation serial production systems are difficult to build and solve. Based on the insights obtained from a two-station continuous materials flow production line, a heuristic is developed to approximate the production rate of longer lines.