Part Processing Time Research Articles

Reliability assessment of multistate flexible manufacturing cells considering equipment failures

The reliability evaluation of a flexible manufacturing cell (FMC) is valuable for engineers in comprehending the system's reliability level and making well-informed decisions. Nevertheless, the inherent randomness and heterogeneity in the FMC production process present challenges in assessment, making traditional reliability evaluation metrics designed for single machines partially inadequate. This study conducts a comprehensive analysis of various FMC states, encompassing normal operation, failure downtime, and non-failure idle time. Additionally, variables such as part processing time, part transportation time, and equipment maintenance time are treated as stochastic variables conforming to an exponential distribution. Markov processes are employed to model the production processes of both FMC types, with closed solutions for steady-state conditions derived. This analytical approach facilitates a more streamlined and precise computation of reliability metrics as compared to simulation analysis. As a result, reliability evaluation metrics including equipment utilization, manufacturing capacity, and productivity are utilized to assess FMC reliability. Calculation methods for these metrics are established based on the derived analytical solutions. Furthermore, a practical case study is presented to illustrate and validate the proposed model. The primary contribution of this paper is the provision of a stochastic process modeling approach for FMCs, along with system-level reliability assessment indicators and their corresponding calculation methods. This empowers engineers to efficiently and effectively evaluate FMC reliability within the context of their production processes, facilitating informed decision-making.

Laser debinding of parts produced through material extrusion additive manufacturing

A novel cost effective material extrusion additive manufacturing method for metals and ceramics employs filaments embedded with powdered granules which are shaped, debinded, and sintered sequentially until completion of the part. One well known drawback of the technology lies in the time-consuming debinding process, which often requires handling toxic agents (e.g. acetone, cyclohexane, nitric or oxalic acids), as well as complex heating profiles. Debinding is traditionally done after shaping the part, and little investigation has been made to develop the technology to debind locally, in situ, without the use of toxic consumables. Here, we show that full debinding can be achieved efficiently on the bulk of the printed part through an application of local energy by applying it selectively on the top surface, layer by layer, along the 3D volume of as built green parts. A low intensity infra-red laser is integrated in a custom-built machine to create a hybrid device that combines traditional filament extrusion additive manufacturing with in-situ debinding. The results show that the main binder matrix of a Highly Filled (HF) commercially available stainless steel 316L filament can be removed efficiently along the full volume of the part via laser ablation of the organic mass. Defects, surface roughness and topography deviations can be minimized compared to other traditional thermal debinding methods, further showcasing the capability of building consecutive layers on top of a previously debinded layer. We report improvements in debinding time by a magnitude of 248 % compared to traditional thermal debinding, of 595 % compared to solvent debinding at 45 °C, and 943 % compared to solvent debinding at room temperature. The effect of debinding with the use of lasers in-situ, layer by layer, and the effect in the layer adhesion of fully debinded parts, is investigated through optical and electron microscopy, as well as quantifying the binder mass loss. Debinding in-situ offers new routes to reduce processing times of parts produced through FFF.

Monitoring the Production Information of Conventional Machining Equipment Based on Edge Computing.

A production status monitoring method based on edge computing is proposed for traditional machining offline equipment to address the deficiencies that traditional machining offline equipment have, which cannot automatically count the number of parts produced, obtain part processing time information, and discern anomalous operation status. Firstly, the total current signal of the collected equipment was filtered to extract the processing segment data. The processing segment data were then used to manually calibrate the feature vector of the equipment for specific parts and processes, and the feature vector was used as a reference to match with the real-time electric current data on the edge device to identify and obtain the processing start time, processing end time, and anomalous marks for each part. Finally, the information was uploaded to further obtain the part processing time, loading and unloading standby time, and the cause of the anomaly. To verify the reliability of the method, a prototype system was built, and extensive experiments were conducted on many different types of equipment in an auto parts manufacturer. The experimental results show that the proposed monitoring algorithm based on the calibration vector can stably and effectively identify the production information of each part on an independently developed edge device.

Decision-Making Model of Mechanical Components in a Lean–Green Manufacturing System Based on Carbon Benefit and Its Application

The key to achieving low-carbon manufacturing is to effectively reduce the carbon emissions of production systems and improve carbon benefits. The use of lean and green tools aids in measuring the added value of products, and increases the efficiency and sustainability of production systems. To address this problem and verify that the synergetic relationship between lean and green innovation increases the efficiency and sustainability in production systems, a new low-carbon manufacturing evaluation indicator—carbon benefit—in lean manufacturing systems was discussed. A low-carbon decision-making model of multiple processes aiming at carbon benefit maximization, as well as the dynamic characteristics of carbon benefit and sustainable process improvements in a lean production system, was established. A case study of a certain satellite dish parts manufacturing line was introduced to analyze and verify the feasibility of the proposed model. After improvement, the processing time of unit parts was reduced from 63 s to 54 s. The workstations were optimized again according to the lean–green manufacturing concept, and the number was reduced by 37.5%. The process was recombined and reduced from 8 to 5 to achieve continuous-flow processing. This reduced the distance by 77 m, and at the same time, the number of operating personnel was reduced, and the after-improvement carbon efficiency increased from 12.98 s/kg CO2e to 36.33 s/kg CO2e in comparison with that before the improvement. The carbon benefit after improvement was 193.92% higher than that before the improvement.

Production systems with cycle overrun: modelling, analysis, improvability and bottlenecks

Production systems literature usually attributes throughput losses to two reasons: unreliable equipment and random part processing time (also referred to as machine cycle time). In practice, however, one more reason for throughput losses is observed: cycle overrun. The specificity of cycle overrun is that not all parts may require more time than allotted by a fixed cycle time and, if the overrun does occur, its duration is coupled with the part processing time: typically, it is a fraction or a small multiple of the cycle time. This paper is indented to develop methods for analysis and improvement of production systems with unreliable machines and cycle overrun. Specifically, it introduces a mathematical model of an unreliable machine with cycle overrun, develops its simplified version, explores the efficacy of machines' improvability by reducing either downtime or cycle overrun, and discusses the issue of bottleneck identification. These results are obtained under the exponential assumption on machine reliability and overruns and then extended to the non-exponential case. Finally, the methods developed are illustrated by a case study based on an automotive transmission case machining line.

Параметризация переходов точения

Время обработки и стоимость заготовки являются наиболее важными для завода, это показатели, которые отражают эффективность обработки и заинтересованность завода. Очень важным направлением исследований является определение стоимости и времени обработки деталей по изменению некоторых параметров. При использовании программного обеспечения "SAPR_2020" для проектирования токарной обработки, можно настроить независимые переменные и проанализировать стоимость обработки и время обработки, что значительно облегчает исследование токарной обработки. Час оброблення і вартість заготовки є найбільш важливими для заводу, це показники, які відображають ефективність оброблення і зацікавленість заводу. Дуже важливим напрямком досліджень є визначення вартості і часу оброблення деталей при зміні деяких параметрів. При використанні програмного забезпечення "SAPR_2020" для проектування токарного оброблення, можна налаштувати незалежні змінні і проаналізувати вартість оброблення і час оброблення, що значно полегшує дослідження токарного оброблення. The processing time and the cost of the workpiece are the most important for the plant, these are indicators that reflect the processing efficiency and the interest of the plant. A very important area of ​​research is the determination of the cost and processing time of parts by changing some parameters. When using the "SAPR_2020" software for turning design, you can set up independent variable and analyze the machining cost and machining time, which greatly facilitates the study of turning.

Additive Manufacturing Processing of Plastics for Mass Production of Composites Tooling: Technical and Economic Analysis

AbstractThe present paper focuses on the use of several additive manufacturing (AM) techniques for tooling manufacturing for composite parts production. A geometry that prevents mandrel removal is selected and it is analyzed in a real industrial environment for composites production using autoclave molding. The use of two different AM mandrels is evaluated: fused deposition modeling and liquid crystal display. The results are analyzed in terms of composites part quality, processing time and final part cost.

Fast and meta heuristics for part selection in flexible manufacturing systems with controllable processing times

This study addresses a part selection problem for flexible manufacturing systems in which part processing times are controllable to optimize the total cost associated with energy consumption, operational performance, and so on. The problem is to determine the set of parts to be produced, part processing times and the number of tools for each tool type in each period of a planning horizon while satisfying processing time capacity, tool magazine capacity and tool life restrictions. The objective is to minimize the sum of part processing, earliness/tardiness, tool and subcontracting costs. Tool sharing among part types is also considered. After an integer programming model is developed, two types of solution algorithms are proposed, that is, fast heuristics useful when decision time is critical and variable neighborhood search algorithms when solution quality is important. Computational experiments were conducted on a number of test instances and the best fast heuristics are specified, together with reporting how much the variable neighborhood search algorithms improve the fast heuristics.

Nash-equilibrium algorithm and incentive protocol for a decentralized decision and scheduling problem in sustainable electroplating plants

This paper addresses a decentralized production decision and scheduling problem in smart electroplating plants considering environmental sustainability. Due to the characteristics of the electroplating process, part processing times are confined to time-window constraints and controlled by independent autonomous agents with the support of multi-agent and distribution manufacturing technologies. It is shown that part processing times in chemical/physical tanks not only determine the productivity but also affect the environmental cost. Hence, two essential issues should be addressed: (a) how to find equilibrium strategies of agents (i.e., part processing times) in such a decentralized manufacturing setting; and (b) how to design an incentive protocol inducing the equilibrium strategies towards the optimal ones concerning the productivity and the environmental cost simultaneously. To deal with the first issue, this paper establishes a non-cooperative sequential game model, which simulates the evolution process of the strategies from an unstable state to an equilibrium one. Then, an iterative algorithm is developed to find Nash equilibrium strategies based on a cyclic bi-value graph. To address the second issue, a novel heuristic rule is proposed for the incentive protocol by exploring the characteristics of time-window constraints and environmental cost functions. The results of numerical experiments validate the performance of the Nash-equilibrium algorithm and the effectiveness of the heuristic rule.

Robust optimization to design a dynamic cellular manufacturing system integrating group layout and workers assignment

In this paper, a robust optimisation approach is proposed to solve a mathematical model integrating cell formation, group layout and operators assignment decisions under a dynamic situation. The main aim of applying a robust approach is to obtain an optimal design of a cellular manufacturing system that is robust with respect to encountered uncertainties in part demands and processing times. The integrated model incorporates several design attributes including operations sequence, group layout, equal-area facilities multi-rows layout, flexible cell reconfiguration, operators hiring/firing and training, operator available time, limitations of cell size and uncertain processing times and part demands. Two illustrative numerical examples are solved to investigate the validity of the robust model. Regarding the NP-hardness of the proposed model, an efficient simulated annealing algorithm is implemented. Some test problems either generated randomly or taken from the literature are solved and the results are compared with the ones obtained using CPLEX. [Received: 31 May 2019; Accepted: 3 May 2020]

Multiple item batch scheduling model on a batch processor to minimize total actual flowtime parts through the shop

This research is to address a problem of scheduling batches consisting of multiple item parts processed on a batch processor where each item requires a certain processing time which may differ from others. A number of parts are defined as a batch and processed simultaneously with sharing a set up time. A batch can be formed of the parts with different type of item and the processing time of batch equals the longest processing time of parts in the batch. It is assumed that an excessive duration of processing the parts will not lead to any defect, but increase the operating cost. The completed part must simultaneously be delivered at common due date, d. The objective is to minimise total actual flowtime of parts through the shop. A solution procedure to solve the problem is proposed and numerical examples are shown.

Hybrid manufacturing of components from Ti-6Al-4V by metal forming and wire-arc additive manufacturing

Abstract The manufacturing of components from the titanium alloy Ti-6Al-4 V is of great significance for many industrial sectors. The production of high-performance Ti-6Al-4 V components typically requires multiple hot forging steps and leads to parts with tolerances that need extensive machining to create the final shape. For many applications, net-shape technologies such as additive manufacturing (AM) could enable a higher material yield. However, with the part size, cost and processing time in AM rise rapidly. Thus, the advantages of AM and forging operations could be exploited by combining both processes to new hybrid process chains. The present study investigates the use of Wire-Arc additive manufacturing (WAAM) for hybrid manufacturing of Ti-6Al-4 V aerospace components. Two process routes are investigated that combine forming and AM processes. In the first process route, a WAAM process is used to generate a pre-shaped semi-finished part. The semi-finished part will then be forged using a single forming tool to obtain the final part contour. The second process route utilizes a conventionally forged pre-form, onto which features of the final workpiece are added using WAAM. The results confirm that hybrid technologies combining WAAM and forging are very promising for Ti-6Al-4 V part production. A jet engine blade produced by WAAM and subsequent forging shows microstructures typically produced in conventional processing of Ti-6Al-4 V alloy and exhibits tensile properties, which exceed the specification level of cast and forged Ti-6Al-4 V material. Features created by WAAM on forged pre-forms are shown to reach the mechanical properties required to combine both technologies. The combination of WAAM and forging may hence be used to develop new manufacturing chains that allow for higher material yield and flexibility than conventional forging.

Microwave processing of carbon fibre polymer composites: a review

Microwave processing of carbon fibre-reinforced polymer (CFRP) composites is gaining increasing attention as an alternative to conventional thermal processing techniques. It has the potential to reduce part processing times and alleviate the bottleneck that often exists in composite component production. The present study reviews the current research and the state-of-the-art of microwave processing of CFRP composites. The benefits and limitations of microwave processing compared with traditional thermal processing methods are examined. The mechanical properties of microwave-cured composites are compared against conventionally-cured counterparts with varying levels of success. Current industrial microwave heating technologies are also examined. It is evident that microwave processing of polymer composites is promising but has notable limiting factors which have stunted its uptake in industry. Due to their prevalence in literature, CFRP composites with thermosetting matrices are the focus of this review. However, potential applications to carbon fibre-reinforced thermoplastics are also briefly described.

Wire Vibration Modeling and Experimental Analysis for Wire Saw Machining

Abstract Surface roughness is the key index point of wire saw processing silicon carbide (SiC). Many factors influence wafer surface quality, which is determined by the motion of the wire relative to the part. The vibration characteristic of wire saw and the process parameters are concerned factors in this paper, which presents a wire vibration model to study the wire saw vibration law. Experimental studies of a stationary wire are conducted to calibrate the damping coefficient and experimental studies of a moving wire are used to validate the developed model. Simulation, theoretical, and experimental data for wire vibrations during a variety of machining processes are found to compare very well, and the effects of various wire saw process parameters are investigated to analyze the influences of process parameters on wire vibration. It was shown that increasing the wire tension and feed rate, or decreeing the wire length, decreases the wire's first dominant frequency, and that changes in the wire velocity had a negligible effect. Finally, the measurement of the surface morphology and wire saw vibrations for different processing parameters was conducted, and it was seen that increases in the wire velocity and wire tension increases part surface quality and decreases processing time, while an increase in the feed rate decreases both part surface quality and processing time. The results show a clear correlation between the amplitude of the wire vibration outside of the processing zone and the part surface quality.

Batching and scheduling for a single-machine flexible machining cell with multi-fixturing pallets and controllable processing times

This study addresses an integrated batching and scheduling problem for a single-machine flexible machining cell in which each pallet can load multiple parts, i.e. multi-fixturing pallets, and part processing times can be changed with different processing costs, i.e. controllable processing times. The batching sub-problem is to select the set of parts to be produced in each period of a planning horizon and the resulting scheduling sub-problem is to determine the set of parts to be loaded on each multi-fixturing pallet, the part processing times and the pallet input/processing sequences for the parts selected in each period. A bi-criterion objective is considered that minimises the total tardiness and the total processing cost simultaneously. A solution approach is proposed that consists of three phases from the first to the last period: (a) generating the whole schedule over the planning horizon; (b) selecting the parts to be produced during the current period using the scheduling information; and (c) determining the final schedule for the selected parts. Simulation experiments were done on a number of test instances and the results are reported.

Implementation of fuzzy system using hierarchical Colored Petri Nets to model flexible manufacturing cell

In Flexible manufacturing field the Fuzzy application found in to solve conflict situation, production routing, and control in the system. In present days, to produce a product according to the Delivery dates is an important issue in Flexible Manufacturing industry. In order to focus on this issue, we try to solve this problem by implementing fuzzy rules according to due dates. The fuzzy rules are divided in three sections such as Early Due Dates (EDD), Exact Due Dates (EXACT), and Over Due Dates (OVER). In this flexible cell two other parameters are part processing time and the number of tools which are described in this fuzzy rules model. The part processing time and the number of tools are described with the small, medium and large linguistic variables. The fuzzy rule based model is constructed using Hierarchical Colored Petri Nets which is suitable to define each section as a sub model. The observed results provide the overall analysis and performance of cell. The constructed manufacturing cell model also provides the detailed behaviour of each resource where resource appears as Color token values. Also, we compare the simulation results from Hierarchical Fuzzy Colored Petri Nets and Matlab fuzzy rule based design for flexible cell.

다중치구 장착 팔렛과 가변 가공시간을 고려하는 유연제조셀에 대한 이중 기준 스케줄링

This study considers a scheduling problem for a single machine flexible machining cell in which each pallet can load multiple parts and part processing times are controllable with different processing costs. The problem is to determine the set of parts to be loaded on each pallet, the part processing times, the pallet input sequence and the pallet processing sequence. To investigate the trade-off between part processing cost and scheduling performance, we consider a bi-criterion objective of minimizing the total processing cost and the total flow time. A two-stage solution approach is proposed in which part loading/pallet input sequencing are done using a priority rule and part process timing/pallet process sequencing are done using an iterative heuristic. Simulation experiments were done, and the results show that the two-stage solution approach gives better Pareto solutions than the rule combination based solution approach.

A decomposition method for efficient manufacturing of complex parts

ABSTRACTThis paper presents a method to decompose three dimensional complex parts into readily available stock material to take advantage of advanced joining to build up a rigid assembly. The method generates many alternative assemblies by decomposing the solid geometry iteratively with cutting planes. Each assembly is then evaluated based on cost. The process continues until the developed search algorithm converges on a near optimal solution. Application of this method will reduce material waste, thus reducing per part processing time, energy consumption, and associated production costs. Example parts for a variety of metals show how the computational tool finds near optimal solutions for complex three dimensional solids.

A hybrid method based on genetic algorithm and dynamic programming for solving a bi-objective cell formation problem considering alternative process routings and machine duplication

Cell formation is one of the first and most important steps in designing a cellular manufacturing system. It consist of grouping parts with similar design features or processing requirements into part families and associated machines into machine cells. In this study, a bi-objective cell formation problem considering alternative process routings and machine duplication is presented. Manufacturing factors such as part demands, processing times and machine capacities are incorporated in the problem. The objectives of the problem include the minimization of the total dissimilarity between the parts and the minimization of the total investment needed for the acquisition of machines. A normalized weighted sum method is applied to unify the objective functions. Due to the computational complexity of the problem, a hybrid method combining genetic algorithm and dynamic programming is developed to solve it. In the proposed method, the dynamic programming is implemented to evaluate the fitness value of chromosomes in the genetic algorithm. Computational experiments are conducted to examine the performance of the hybrid method. The computations showed promising results in terms of both solution quality and computation time.

Build Orientation Determination for Multi-material Deposition Additive Manufacturing with Continuous Fibers

Build orientation of a part in Additive Manufacturing (AM) has complex effect on part's quality, process planning, post-processing, processing time and cost, etc. The identification of the optimal build orientation for a part is one of the main contents of process planning in AM. In this paper, a build orientation optimization strategy is developed for a new AM process, multi-material deposition with continuous fibers, to improve the part quality while reducing the production time & cost. First, a set of finite alternative build orientations are generated by using surface shape feature with associated rules derived from the specific characteristics and constraints of the new developing AM process; then, a multi-attribute decision making algorithm is applied to determine the optimal orientation according to preset preferences. A case study is presented for demonstration.