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Over the last decade or so a group of us, while working at Bell Labs, have been able to develop a large number of silicon micromachines for a wide range of applications. In this article, which is part of a special volume to celebrate the career of Professor Francis Gasparini who is an old friend and colleague, we review the devices we have been able to build and discuss their applications. These applications range from scientific experiments looking at single vortex dynamics and the observation of the Casimir effect to technological applications such as a large, all-optical switch. In this article we make the point that MEMS devices and VLSI processing are the “New Physics Machine Shop”.

Keeping a record of operator experience remains a challenge to operation management and a major source of inefficiency in information management. The objective is to develop a framework that enables an explicit presentation of experience based on information use. A purposive sampling method is used to select four small and medium-sized enterprises as case studies. The unit of analysis is the production process in the machine shop. Data collection is by structured interview, observation and documentation. A comparative case analysis is applied. The findings suggest experience is an accumulation of tacit information feedback, which can be made explicit in information use interoperatability matrix. The matrix is conditioned upon information use typology, which is strategic in waste reduction. The limitations include difficulty of participant anonymity where the organisation nominates a participant. Areas for further research include application of the concepts to knowledge management and shop floor resource ...

A 10,000-Year Clock, a monument-size mechanical clock designed to measure time for 10 millennia is discussed. Danny Hillis, an electrical engineer with three degrees from MIT who pioneered parallel super computers at Thinking Machines Corp., worked for Walt Disney Imagineering, and then cofounded the consultancy Applied Minds, dreamed up the project in 1995 to get people thinking more about the distant future. But the clock is no longer just a thought experiment. In a cluttered machine shop near a Starbucks in San Rafael, Calif., it's finally ticking to life.

ON APRIL 13, 2011, Yale University senior Michele Dufault, an astronomy and physics major, died after her hair caught in a lathe in a university machine shop. In response to the incident, Yale initiated a review of its policies concerning student access and use of machine shops and released its updated rules over the summer. The new policies divide shop tools and equipment into categories based on their potential hazards, allow student access based on those categories, largely prohibit working alone, and require safety review of machine shop projects before students can begin work. The new policies are an objective and risk-based approach to machine shop access and safety, says Laurence Doemeny, chair of the American Chemical Society Committee on Chemical Safety . After Dufault’s death, Doemeny informally surveyed a number of university shop policies available online. Yale’s updated program is similar to other shop programs he can recall, he says. Doemeny also notes ...

Factory approval test (FAT) or shop run test is a unique opportunity to evaluate rotating machine performance before delivery to site. This note presents a new adaptive signal processing method to evaluate vibration measurement during FAT based on obtained noisy data. It is also a necessary step for machine reliability, fault diagnosis, future predictive maintenance, and condition monitoring.

This paper considers a coordinated scheduling problem. For the first-stage transportation there is a crane available to transport the product from the warehouse to a batching machine. For the second-stage transportation there is a vehicle available to deliver the completed jobs from the machine shop floor to the customer. The coordinated scheduling problem of production and transportation deals with sequencing the transportation of the jobs and combining them into batches to be processed. The problem of minimizing the sum of the makespan and the total setup cost was proven by Tang and Gong [1] to be strongly NP-hard. This paper proposes two genetic algorithm (GA) approaches for this scheduling problem, with different result representations. The experimental results demonstrate that a regular GA and a modified GA (MGA) can find near-optimal solutions within an acceptable amount of computational time. Among the two proposed metaheuristic approaches, the MGA is superior to the GA both in terms of computing time and the quality of the solution.

The strategy games have been traditionally applied in the teaching of subjects related with “decisions making”, principally in the university studies related with the company. Nevertheless, the potential of this methodology makes also applicable to studies that lead to applicable practices in companies or factories, like happens with the technical educations. So, the present paper shows the methodology applied in the teaching of “Engineering Plant”, inside the Official Master of Manufacturing Engineering in the University of Cadiz, circumscribing it in a context of a material forming machine shop by chip removal. During the experience, distributions by process and by product have been simulated, determining the fictitious domain to pass from one to another. This was preceded by the determination of the. Finally, the discussion has driven to emphasize the importance of the reduction of dead-times due to the movements.

An analysis of the factors that govern the metrological characteristics of magnetic induction and eddy-current thickness indicators used in the measurement of protective metallic coatings and the reliability of the results of measurements performed with the use of these types of gauges under the conditions of a machine shop is presented.

This study reviews some of the existing work in fuzzy multi-criteria decision making. According to the literature review, there is no research found in sequence selection in a single machine shop. The aim of this study is to select the best sequence in a single machine shop by fuzzy AHP. In the present paper, after introducing the efficiency indices in operation sequencing selection and a brief description of the fuzzy analytic hierarchy process method the way of using it is mentioned. The sequence calculated by the NBR algorithm is selected as the best sequence. The sequences calculated by the NBR, minimizes the launching and setup costs of the equipment.

The production environment of aerospace industry is make-to-order. The life cycle of aircraft is more than 20 years. Aircraft parts should have higher precision and lightweight to achieve the requirements of safety, payload, and controllability. Machine parts are the important portion of aero-structures. Base on the strength, function, contour of machine parts, then assign to suitable machine center for machining. This study construct the shop floor control mechanism of aerospace machine shop which combine the concept of order release control, gateway control, queue level control, color code control, cycle time control, and apply the on-time dispatch and on-time completion as an indicator to monitor the performance of shop floor control. Thus, we can improve the weakness and increase the competitive advantages of machine shop in the global competitive aerospace market.

Factory approval test (FAT) or shop run test is a unique opportunity to evaluate rotating machine performance before delivery to site. This paper presents a new signal processing method to evaluate vibration measurement during FAT or shop run test based on recorded noisy data. It is also a necessary step for machine reliability, fault diagnosis, future predictive maintenance and condition monitoring.

To meet the rising demands for pure customization of products, new approaches for automated fabrication of customized part geometry are needed, on both the software and hardware side, that balance flexibility, robustness and efficiency. This is a great challenge since today it requires significant human expertise supported, only partially, by computer-aided approaches. This paper introduces a new approach and framework for an autonomous design-to-fabrication system that integrates cognitive capabilities, such as reasoning from knowledge models and autonomous planning, and embeds these in the machines themselves to automatically fabricate customized parts. The framework integrates into a common process automatic workpiece selection using an ontology, generative CNC machining planning using shape grammars and automated fixture design, based on a novel flexible fixture device hardware. Initial results are given for the machining planning approach applied to 2.5D parts with a defined approach direction and the prototyped fixture device is presented. The advantages and potential of the framework stem mainly from applying the principles of cognitive technical systems to a fabrication system to develop an integrated and on-line approach. The methods are developed specifically for use on the machine shop floor to take advantage of the possibility to update and extend knowledge models to reflect current fabrication capabilities and to adapt to changes in the environment and re-plan during operation. Finally, future directions, including integrating on-line perception and learning, are discussed, which are required to create a truly flexible and cognitive fabrication system.

Research has demonstrated that inductive learning promotes deep knowledge structures, critical thinking and intellectual development. Industrial employers seek graduates with integrated knowledge and hands-on skills. This paper shows how a project-oriented machine shop practice course has been integrated with other courses, following an active and inductive learning model. Specific projects included a fast-return actuator, a simple acoustic guitar, a compressed-air engine and a catapult. These projects were chosen and executed to interface with concurrent and future courses, adding depth, ownership, enthusiasm and an experiential basis for the entire learning experience. Assessment data indicate high course value and support for future coursework. This model transforms the traditional, deductive learning model into inductive and active learning.

This paper presents a decision-making approach towards adaptive setup planning that considers both the availability and capability of machines on a shop floor. It loosely integrates scheduling functions at the setup planning stage, and utilizes a two-step decision-making strategy for generating machine-neutral and machine-specific setup plans at each stage. The objective of the research is to enable adaptive setup planning for dynamic job shop machining operations. Particularly, this paper covers basic concepts and algorithms for one-time generic setup planning, and run-time final setup merging for dynamic machine assignments. The decision-making algorithms validation is further demonstrated through a case study. Note to Practitioners-With increased product diversification, companies must be able to profitably produce in small quantities and make frequent product changeovers. This leads to dynamic job shop operations that require a growing number of setups in a machine shop. Moreover, today's customer-driven market and just-in-time production demand for rapid and adaptive decision making capability to deal with dynamic changes in the job shop environment. Within the context, how to come up with effective and efficient setup plans where machine availability and capability change over time is crucial for engineers. The adaptive setup planning approach presented in this paper is expected to largely enhance the dynamism of fluctuating job shop operations through adaptive yet rapid decision makings.

This paper presents an application of a two level mixed optimization method on a machine scheduling problem of a government owned machine shop. Where evolutionary algorithm methods are suitable for solving complex, discrete space, and non-linear, discontinuous optimization problems; classical direct-search optimization methods are suitable and efficient in handling simple unimodal problems requiring less computation. Both methods are used at two levels, the first level decides which machines to be used for the machining operations and how much overtime (at extra cost) to be allotted to each work order, the second level decides for which operation and on which day the overtime should be allotted so as to attain its maximum benefit. A sample problem has been solved by using the above methods and a range of non-dominated solutions have been presented in a tabular form to enable the production manager to choose his options based on the given criticality of the work order.

The focus of this paper is customer order scheduling (COS) problem, where each order consists of a set of jobs that must be shipped as one batch at the same time. In COS each job is part of a customer order and the make-up of the jobs in the order are pre-specified. Most of the existing research deals with COS in a single machine or in a parallel machine shop for developing an optimal solution. COS is common in a normal job shop, and the more complex the shop, the more complex the scheduling. Most existing research has focused on trying to reduce the completion time of the batch. That is, the focus is only on the point in time the last job is finished, while ignoring the actual duration of the jobs within the same order. The longer it takes to complete all the jobs within an order the more it increases the stock of finished goods and the more it deteriorates the efficiency of the logistics and the supply chain management. A new dispatching rule, referred to as Minimum Flow Time Variation (MFV), has been proposed for COS in a normal job shop, in order to reduce the total time it takes to complete all jobs within the same order. That is, the individual completion times of all jobs for the same customer order will be controlled in order to improve the shipping performance. In the simulation test and statistical analysis, the level of work in process (WIP) under the MFV rule in the finished goods warehouse is reduced by more than 70% compared to any other method. The MFV method will efficiently reduce the stock level of finished goods, and controls the waiting time required before they can be shipped. Depending on the environmental factors, the performance of our proposed method will become increasingly significant the more complex the system.

We have studied the scheduling of automated guided vehicles (AGVs) for efficient and uniform material distribution from a truck-dock to machining units of the machine shop in an automotive manufacturing plant. The material distribution problem, being a much simpler special case of the more general material transfer problem, is easily amenable to analysis. We have assessed the number of AGVs required to meet the total material requirements of all the machining units in the shop. Proposing innovative dispatch rules, we have evaluated their performance in simulation by monitoring parameters reflecting efficiency and uniformity of material distribution, both for single AGV and multiple AGV case. In multiple AGV case, we introduce the notion of zones having comparable demands for AGV, and assign one AGV to each zone, so that each AGV can operate largely independently--sharing a minimum path with other AGVs using deadlock avoiding protocols. The results of simulation runs and their implications are discussed.

This paper presents a method for cost optimum conversion of functional tolerances into machining tolerances transferred to one or more datum reference frames. A new concept—that of the Tolerance Element—is introduced as a machining process-related geometric entity with attributes associated with the accuracy cost. The accuracy-getting capabilities and cost per Tolerance Element are recorded for a particular machine shop through an appropriately designed database feedback form. The Tolerance Elements methodology, once adapted for this machine shop through processing information of the database feedback form, automatically creates application-focused cost-tolerance functions. The latter, in conjunction with the tolerance transfer principle and the machining axes accuracies, are used for the formulation of the problem objective function for cost optimum tolerancing. The system database needs expert updating only when changes occur in the machine shop facilities and/or expertise. The proposed method ...

A virtual reality machine shop environment was developed and integrated with a graphical model for the calculation of quantitative data affecting the roughness of a machined surface. During the machining process simulation in the virtual environment, material removal and milling machine axes kinematics are visualized in real time and qualitative parameters related to the process feasibility are evaluated. The model determines the machined surface topomorphy as a cloud of points retrieved from the visualization system Z buffer and surface roughness is calculated. The current study is focused on the methodology for the verification of the quantitative data acquired by the system. Results were verified with data determined in cutting experiments and by another numerical model that was integrated into the system. The results were found to be in agreement with both the numerical model and the experiments.

This paper considers due date assignment and sequencing for multiple jobs in a single machine shop. The processing time of each job is assumed to be uncertain and is characterized by a mean and a variance with no knowledge of the entire distribution. A heuristic procedure is developed to find job sequence and due date assignment to minimize a linear combination of three penalties: penalty on job earliness, penalty on job tardiness, and penalty associated with long due date assignment. Numerical experiments indicate that the performance of the procedure is stable and robust to job processing time distributions. In addition, the performance improves when the means and variances of job processing times are uncorrelated or negatively correlated or when the penalty of a long due date assignment is significant.

Having a dedicated place to work on your projects is helpful. Set up a software environment and a place to do hardware engineering at the same time. Be careful to keep your machine shop separate from your ARTIK or development workstation. Dropping metal filings onto electronic circuit boards is a recipe for disaster. Keep the two workspaces apart as far as possible.

Hard turning is a finish machining process used to replace the grinding of hardened component in the shop floor as grinding has its inherent problems like requirement of multiple passes and environmental hazards due to coolant used to name a few. Hard turning is fast and environmental friendly process and can produce a surface finish comparable, sometime even better surface finish than grinding. But hard turning has its own problems, which make its use limited on the shop floor. The surface integrity issues like hard and brittle white layer generation and tensile residual stress on the machined surface are the main problems encountered in hard turning. Also, the variation in hardness along the subsurface region indicates that the hard turning process leads to in-homogeneity in the steel components. But since the advantages of the process are very lucrative due to shorter finishing times with green manufacturing, researchers have tried to address the shortcomings of the process to make the process stable to be used in the machine shop. This module reviews various surface integrity issues in hard turning and the possible ways to control them.

Analyzing the special job shop scheduling problem of a large-scale machine shop, considering workers operational qualification and characteristics of discretely concurrent production, a novel mathematical model has been proposed to meet actual production. In addition, an improved binary particle swarm optimization (BPSO) algorithm has been developed for solving the problem of arranging m workers to process n structures, to optimize the minimum completion time of the jobs. In this improved BPSO, a new method of making initial particles has been presented for searching the optimum particle in the feasible dimensional problem space. Besides, importing memory base, modifying Sig function, and considering constraint condition have been used in the algorithm for making updated particles meet the constraint equation of the mathematical model. The research on the algorithm examples demonstrates that the improved BPSO algorithm is effective and can achieve good results. Moreover, the mathematical model has wide application in discrete manufacture.

A new navigation method that decouples manufacturing processes of tailor-made products has been developed for shortening lead time. Axiomatic Design expresses manufacturing processes with two design equations; one with functional requirement (FR) of “defining process” and design parameter (DP) of “decisions in process,” and the other with FR of “predicting completion time of product” and DP of “priority of product.” Once formulated, decoupling the system with the rules of “No feedback” and “No moving up” effectively shortens lead time. Applying the navigation methodology to a real unmanned machine shop of molds, eventually shortened it from 44 to 7.7 days.

In order to investigate the temporal and steady-state low-frequency characteristics of sound in industrial workshops, measurements were made of reverberation times and sound-pressure levels in a machine shop and in a 1/8-scale-model workshop when empty and fitted. Low-frequency pure tones and octave-band noise were used as the source excitation. Fittings generally reduced reverberation times. In the empty machine shop, levels showed strong spatial variations due to modal effects, as expected. When fitted with machine tools, levels changed by up to 20 dB, and local variations increased, despite the fittings being small compared to the sound wavelengths. In the scale model, smaller and larger fittings were tested. Results for the model when empty and when fitted with the larger fittings were similar to those in the machine shop. With the smaller fittings, the results suggested that fittings can act to diffuse sound, reducing spatial variations. Tests were also done in an empty and fitted hemi-anechoic chamber to study the effect of fittings in the absence of the room. Fittings alone only slightly affected the sound field, demonstrating that modal effects are predominantly due to the room, possible modified by the presence of fittings.

This paper presents an integrated optimization model of production planning and scheduling for a three-stage manufacturing system, which is composed of a forward chain of three kinds of workshops: a job shop, a parallel flow shop consisting of parallel production lines, and a single machine shop. As the products at the second stage are assembled from the parts produced in its upstream workshop, a complicated production process is involved. On the basis of the analysis of the batch production, a dynamic batch splitting and amalgamating algorithm is proposed. Then, a heuristic algorithm based on a genetic algorithm (known as the integrated optimization algorithm) is proposed for solving the problem. Note to Practitioners-This paper presents a method for integrated production planning and scheduling in a three-stage manufacturing system consisting of a forward chain of three kinds of workshops, which is common in such enterprises as producers of automobiles and household electric appliances, as in the case of an autobody plant usually with the stamping workshop, the welding and assembling workshop, and the painting workshop. Herein, the production planning and scheduling problems are simultaneously addressed in the way that a feasible production plan can be obtained and the inventory reduced. A batch splitting and amalgamating algorithm is proposed for balancing the production time of the production lines. And a case study of the integrated planning and scheduling problem in a real autobody plant verifies the effectiveness of our method

Building 431 at the Puget Sound Naval Shipyard & Intermediate Maintenance Facility in Bremerton, Washington houses the primary machine shop used to maintain the Navy ships and submarines on the West Coast. The historic 640,000 square foot steel, concrete, wood, and masonry building was constructed in 1935, underwent significant additions during World War II, and has been continually modified since that time. KPFF was the structural engineer on the design team tasked by the Navy to design seismic strengthening for the building that would satisfy the enhanced performance objectives required for this mission-critical structure. The design for the seismic retrofit of the structure began in 2013 using the ASCE/SEI 41-13 Standard (ASCE-41). KPFF employed several interacting design methods to achieve the required performance goals, including nonlinear response history analysis (NLRHA), selective weakening of existing perimeter walls, and 71-foot-long Buckling Restrained Braced Frames (BRBFs) added to the building’s exterior.

The Manufacturing Automation course in a standard engineering education prepares students for the most contemporary production and technology challenges. This paper describes Rapid Prototyping and Modeling done as subtractive and additive manufacturing operations in the scope of the UConn Engineering program, as well as its integration into the Manufacturing Automation course. It is a companion paper with IMECE 2014-38355 [1] that reports how students of Manufacturing Automation are exposed to rapid prototyping. This is done in the UConn School of Engineering Machine Shop, Mechanical Engineering Machine Shop and Laboratory of the desk top modelers. Some experience students gain also in MEM Prototyping Laboratory and during class trips to Pratt & Whitney/ UConn Additive Manufacturing Research Laboratory and to CNC Software Inc Experimental Testing Shop. One of the objectives of the course is to introduce students to the processes of advanced Subtractive and Additive Manufacturing (SM and AM). The CAD/CAM cutting software such as CAMM-3 Micromodeler, G-code and Mastercam were used successfully in those operations. The elements of CAD/CAM software were integrated in the model cutting exercises. Full automation of integrated design and manufacturing data exchange was attempted but was found still not possible to accomplish. However the use of automation software in a sequence, tin tandem with data export and import, marks a significant step forward towards integrated manufacturing automation. The research to accomplish the next level of automation will be continued and the results will be applied to reinforce the teaching and practice of Manufacturing Automation. Significant role in helping students to understand the methods of subtractive and additive manufacturing has cooperation with two Connecticut companies that achieved outstanding results in modeling and prototyping. These are Pratt & Whitney in East Hartford and CNC Software Inc in Tolland, Connecticut. The class visits to their facilities and experience with their equipment played a significant role in understanding of the subtractive and additive machining processes. Efforts to introduce students to the concepts of subtractive and additive machining process are described. Conclusions about the teaching methods of product machining concepts and lessons learned are pointed out.

In manufacturing the solutions found for scheduling problems and the human expert’s experience are very important. They can be transformed using Artificial Intelligence techniques into knowledge and this knowledge could be used to solve new scheduling problems. In this paper we use Decision Trees for the generation of new Dispatching Rules for a Single Machine shop solved using a Genetic Algorithm. Two heuristics are proposed to use the new Dispatching Rules and a comparative study with other Dispatching Rules from the literature is presented.

Many students entering Mechanical or Mechatronics Engineering (MME) at the University of Waterloo (UWaterloo) have limited hands-on skills and lack practical technical knowledge. Student surveys cite a desire for increased practical experience within the curriculum.This paper presents an initiative to address this issue. A keychain project was designed to involve all first year MME students in a practical (hands-on) activity that would foster competence with machinery. This objective proved difficult to implement due to large student enrollment, where scheduling, supervision, and resources were all significant challenges. However, as a result of this experience, over 400 engineering students were provided early exposure to the Student Machine Shop, creating a desire and confidence to pursue additional experience.This program is expected to continue at UWaterloo and become a component of a wider engineering clinic initiative. The methodology and key takeaways will be discussed herein.

This paper outlines a Capstone project, or senior design project, done by Midshipmen at the United States Naval Academy. A preexisting airdrop delivery system was used and modified to include high altitude low opening capabilities. A small fiberglass prototype was fabricated in a machine shop, and simulations with the on-board code followed. Test plans were made for Skydive Delmarva in Laurel, DE. Two jumpers would exit the aircraft with the system and record data as they fell.

The roll forming industry has many difficulties in product development and process set-up. The design and development of rolls and processes are mainly based on trial-and-error and past experiences. Recent industrial trends demand products having high quality and tight tolerances. This requires more precise and cost-effective roll-forming processes than the ones employed in the traditional product development methods. SHAPE is a reliable FE based solution provider, which covers a wide range of roll forming and rotary forming simulations including ring rolling, tube spinning, flow forming, and thread rolling. It also provides powerful analysis tools for heat transfer, roll stress and microstructure analyses. In this chapter the technical capability of SHAPE for roll forming is assessed by studying an industrial problem. The accuracy and robustness of the software is evaluated using machine shop results.

This paper presents a methodology for the automatic establishment and processing of machine shop and application-specific cost-tolerance functions for the cost-optimum allocation of tolerances in dimensional chains. It can be readily integrated into a CAD environment and overcomes inefficiencies of existing systems. The concept of tolerance element (TE) is introduced that is a generic and machining process related geometric entity with attributes clearly identifiable in conformance with the existing industrial understanding. The system database module, based on a database feedback form filled by the machine shop, once created needs updating only when changes occur in machines, facilities and/or the machine shop expertise. An application example demonstrates the concept.

In this paper, we consider the problem of providing flexibility to solutions of two-machine shop scheduling problems. We use the concept of group-scheduling to characterize a whole set of schedules so as to provide more choice to the decision-maker at any decision point. A group-schedule is a sequence of groups of permutable operations defined on each machine where each group is such that any permutation of the operations inside the group leads to a feasible schedule. Flexibility of a solution and its makespan are often conflicting, thus we search for a compromise between a low number of groups and a small value of makespan. We resolve the complexity status of the relevant problems for the two-machine flow shop, job shop and open shop. A number of approximation algorithms are developed and their worst-case performance is analyzed. For the flow shop, an effective heuristic algorithm is proposed and the results of computational experiments are reported.

Disseminative systems are identified as central to the organization and dynamism of humanity's globalized condition. Three types of disseminative systems are defined and their characteristics are delineated in terms of the considerable challenges they pose to comprehensive and effective global governance. The pervasiveness and configuration of disseminative systems presents a further range of conceptual, political, and social difficulties that frustrate a "problem solving" approach, both to the control of disseminative systems themselves and to wider global governance. Without discounting either the potential or the difficulties of conceiving and exercising governance over disseminative systems, the speed and extent of their proliferation and adaptability suggests a fundamental consideration for the development of global governance theorizing: whether its possibilities fall short of the world we have already created. Keywords: disseminative systems, global governance, complexity, connectivity, comprehension. In the aftermath of the Cuban missile crisis, the Pentagon initiated the Nth Country Project, a small initiative to determine whether two amateurs (individuals with doctorates in physics but with no nuclear expertise and no access to classified information) could design a nuclear weapon. As one of the participants recalls, "[after thirty months] we produced a short document that described precisely, in engineering terms, what we proposed to build and what materials were involved. The whole works, in great detail, so that this thing could have been made by Joe's Machine Shop downtown."1 Thirty-five years later, in 1999, the Pentagon's Defense Threat Reduction Agency commissioned Project Bacchus. With little more than a budget and commercial catalogs for laboratory equipment, a team was given the task of assembling a small but functional germ factory. It took them just over a year to produce two

In this paper we study the two-machine flow shop and open shop problems to minimize the makespan with a single interstage transporter that may carry any number of jobs between the machines at a time. For each of these problems we present a best possible approximation algorithm within a class of schedules with at most two shipments. As a by-product of this research, for the problem of minimizing the makespan on parallel identical machines we analyze the ratio of the makespan for a non-preemptive schedule over the makespan of a preemptive schedule. Contributed by the Scheduling/Production Planning/Capacity Planning Department

Regenerative chatter is a major hurdle to the productivity and quality of machining operations. This is because of the undesirable surface finish, excessive tool wear and deteriorated dimensional accuracy. Machining chatter analysis techniques examine the stability of a closed-loop model of machining forces and tool-workpiece system. This model is based on mathematical manipulations of machining forces and the dynamic responses of machining tooling. Almost all techniques derive the dynamic responses from physical test. In this paper, a novel approach of milling chatter stability analysis is introduced by using FEA applications to obtain the dynamic responses of the machine tool. The accuracy of this methodology is validated by machine shop tests.

Presented in the paper is an approach to developing an intelligent mold shop as a means to overcome the difficulties faced by mold-makers due to skill shortages and increased global competition. A machine shop where as much as of the human skills are replaced by a set of intelligent systems is called an intelligent machine shop , and an intelligent mold-making machine shop is called an intelligent mold shop (IMS) . By analyzing the contents of operator’s skill, three intelligent S/W stations have been designed: Technical Data Processing (TDP) Station, Loading Schedule Station, and Real-time Monitoring Station. A detailed architecture of the TDP station is described, and measures of effectiveness of IMS are elaborated.

This paper describes an efficient method to find the lowest cost tool sequence for rough machining free-form pockets on a 3-axis milling machine. The free-form pocket is approximated to within a predefined tolerance of the desired surface using series of 2.5-D layers of varying thicknesses that can be efficiently removed with flat-end milling cutters. A graph-based method finds an optimal sequence of tools for rough machining the approximated pocket. The algorithm used here can be tuned to suit any available tool set and preferred cost models. The tool sequence that is obtained is near optimal, and may take into account tool wear, as well as various overhead costs of the machine shop.

This paper deals with a load-balancing problem among several operators in a semi-automatic parallel machine shop in which two types of machine are operated. The objective is to assign jobs to the proper machines and allocate machines to operators in order to minimize the unbalance of the workloads among operators under the constraints of available machine- and operator-time. There are two types of parallel machines and jobs are classified into the two types. However, operator can handle machines of both types.Although, this situation can be formulated with non-linear integer programming, it is difficult to solve this program. Therefore, a hierarchical heuristic solution procedure is suggested and the performance of the algorithm is evaluated with various data.

Hydraulic pump units are widely used to operate hydraulic actuators. In a typical machine shop, conventional constant speed hydraulic pump units consume more than 20% of the total electric power necessary to operate CNC machine tools. Most of that energy are wasted to run the axial piston pump at idle. This paper describes a variable speed hydraulic pump unit using a switched reluctance motor (SRM), which saves energy drastically. SRM was selected as the most suitable motor for this application. Design and control strategy of this motor are described. Application examples to machine tools shows the effectiveness of the new hybrid pump system in saving energy and in reducing acoustic noise.

The dynamic facility layout problem (DFLP) involves finding an arrangement of facilities that minimises the sum of material handling cost and rearrangement cost over multiple periods. In this paper, the DFLP is modelled as a multiple quadratic assignment problem (QAP), one for each period. Probability-based incremental learning algorithm with a pair-wise exchange local search (PBILA-PWX) is proposed for solving the QAP for each period. The proposed heuristic and 16 algorithms available in the literature are applied for solving a set of 48 benchmark instances of the DFLP. For most of the problem instances, the proposed heuristic provides better results in comparison with an existing robust algorithm. The deviations of the solutions for the proposed heuristic are found to be within 5% of the best known solutions. A case study conducted for determining the machine shop layout of firm manufacturing printing machines is also presented.

In the 1870s, American inventor Thomas Edison forged the first industrial research. At his laboratory at Menlo Park, New Jersey, Edison merged the machine shop with sophisticated electrical and chemical laboratories and employed teams of researchers who could experiment on all aspects of his inventions and move them rapidly from research to development and commercialization.

¾ Six shipyards are in operation under control of Engineering Department of Inland Water Transport. Among them, Dalla shipyard currently accounts for about 50 percent of repair work on ships owned by the Inland Water Transport (IWT). The efficiency of the shipyard, which is about 164 years old, is hampered by old equipment, including some from the WWII-era (Word War II). Now the shipyard needs to be upgraded to improve its current capacity in ship repair. In this study, we proposed two ways which are supporting facilities and re-layout shipyard to increase ship repair. This paper obtains two alternative layouts of shipyard. The first alternative layout does not change the existing layout of shipyard but steel plate warehouse are built. The second alternative changes the existing layout because machine shop and steel plate warehouse is too far from the slipways. The first and second alternatives renovate zone 5 shop, carpenter shop, pipe and boiler shop and repair slipways. The two alternatives have steel plate warehouse as well as the addition of two material handling equipment mobile crane and forklift. The second alternative re-locates new machine shop near the slip ways for better material handling and time consuming. The second alternative is the best alternative in terms of economically feasible, good flow of material and perfect of technical term and the most number of ship repairs. Then it can be improved capacity amount 1.43 times and docking time can be reduced from average 33 days to 27 days.

The National Aeronautics and Space Administration (NASA) has a long term strategy to fabricate components and equipment on‐demand for manned missions to the Moon, Mars, and beyond. To support this strategy, NASA and Made in Space, Inc. are developing the 3D Printing In Zero‐G payload as a Technology Demonstration for the International Space Station (ISS). The 3D Printing In Zero‐G experiment ('3D Print') will be the first machine to perform 3D printing in space. The greater the distance from Earth and the longer the mission duration, the more difficult resupply becomes; this requires a change from the current spares, maintenance, repair, and hardware design model that has been used on the International Space Station (ISS) up until now. Given the extension of the ISS Program, which will inevitably result in replacement parts being required, the ISS is an ideal platform to begin changing the current model for resupply and repair to one that is more suitable for all exploration missions. 3D Printing, more formally known as Additive Manufacturing, is the method of building parts/objects/tools layer‐by‐layer. The 3D Print experiment will use extrusion‐based additive manufacturing, which involves building an object out of plastic deposited by a wire‐feed via an extruder head. Parts can be printed from data files loaded on the device at launch, as well as additional files uplinked to the device while on‐orbit. The plastic extrusion additive manufacturing process is a low‐energy, low‐mass solution to many common needs on board the ISS. The 3D Print payload will serve as the ideal first step to proving that process in space. It is unreasonable to expect NASA to launch large blocks of material from which parts or tools can be traditionally machined, and even more unreasonable to fly up multiple drill bits that would be required to machine parts from aerospace‐grade materials such as titanium 6‐4 alloy and Inconel. The technology to produce parts on demand, in space, offers unique design options that are not possible through traditional manufacturing methods while offering cost-effective, high‐precision, low‐unit on‐demand manufacturing. Thus, Additive Manufacturing capabilities are the foundation of an advanced manufacturing in space roadmap. The 3D Printing In Zero‐G experiment will demonstrate the capability of utilizing Additive Manufacturing technology in space. This will serve as the enabling first step to realizing an additive manufacturing, print‐on‐demand "machine shop" for long‐duration missions and sustaining human exploration of other planets, where there is extremely limited ability and availability of Earth‐based logistics support. Simply put, Additive Manufacturing in space is a critical enabling technology for NASA. It will provide the capability to produce hardware on‐demand, directly lowering cost and decreasing risk by having the exact part or tool needed in the time it takes to print. This capability will also provide the much‐needed solution to the cost, volume, and up‐mass constraints that prohibit launching everything needed for long‐duration or long‐distance missions from Earth, including spare parts and replacement systems. A successful mission for the 3D Printing In Zero‐G payload is the first step to demonstrate the capability of printing on orbit. The data gathered and lessons learned from this demonstration will be applied to the next generation of additive manufacturing technology on orbit. It is expected that Additive Manufacturing technology will quickly become a critical part of any mission's infrastructure.

In this paper, we present results from a study of prehensile human hand use during the daily work activities of four subjects: two housekeepers and two machinists. Subjects wore a head-mounted camera that recorded their hand usage during their daily work activities in their typical place of work. For each subject, 7.45 hours of video was analyzed, recording the type of grasp being used and its duration. From this data, we extracted overall grasp frequency, duration distributions for each grasp, and common transitions between grasps. The results show that for 80 percent of the study duration the housekeepers used just five grasps and the machinists used 10. The grasping patterns for the different subjects were compared, and the overall top 10 grasps are discussed in detail. The results of this study not only lend insight into how people use their hands during daily tasks, but can also inform the design of effective robotic and prosthetic hands.

We consider the problem of scheduling independent jobs on two machines in an open shop, a job shop and a flow shop environment. Both machines are batching machines, which means that several operations can be combined into a batch and processed simultaneously on a machine. The batch processing time is the maximum processing time of operations in the batch, and all operations in a batch complete at the same time. Such a situation may occur, for instance, during the final testing stage of circuit board manufacturing, where burn-in operations are performed in ovens. We consider cases in which there is no restriction on the size of a batch on a machine, and in which a machine can process only a bounded number of operations in one batch. For most of the possible combinations of restrictions, we establish the complexity status of the problem.

The progress of unconventional machining through the application of computer-aided technology is presented. The processes of ECM, EDM, LBM, AWJM are discussed in relation to the influence of CAD, CAM, CAE, CNC, CIM and on their acceptance by manufacturing industry. EDM and LBM can readily be integrated onto the machine shop floor today. Other processes have lesser degrees of automation, mainly because their applications tend to be more specialised. All processes need to be able to be fully automated and integrated if they are to remain competitive.

An exploratory study carried out by researchers in anthropology, workplace health and safety and ergonomics raised questions about the dynamics of knowledge construction in connection with age, experience, culture and work organization. In a machine shop participating in an on-the-job mentoring program, it was observed that official mentors play a secondary role compared to other workers, and that several factors influence mentoring relationships.