Low-volume Production Research Articles

Optimization of production cost for integrating job shop scheduling with production resources

New manufacturing technologies are emerging every day, pushing the bounds of possible and redefining the world around us. This is especially true in the world of computing where much work goes into the design and development of new planning systems, tools, and software packages. This led to the development of various process analysis and manufacturing software packages. Many of these packages use the heuristic methods for solving the problems. Optimization is a design technique in which the best design solution for a problem is seeded using multiple execution and comparison of analysis results. Optimization is carried out for one or more responses acted upon by various constraints. Job shop is an environment for the manufacture of large variety low volume products. In general, the integration of production functional areas with job shop scheduling problems is to be considered as too hard and complex problems. The Production functional areas are Material Requirement Planning, Production Resource Planning, Manufacturing Resource Planning, Employee Time tabling, Human Resource Planning and Lot Size etc. To minimize the loss due to resource allocation, integration of production function resources and job shop scheduling is encouraged. Production resources are resourcing the material, human labours and manufacturing machine tools. Manufacturing assumptions are deployed to found difficult integrated manufacturing systems. In this paper, a hierarchy mathematical modelling approach has been developed to integrate the production resources planning and job shop scheduling. In which, material requirement planning system for material resource arrangement, employee timetabling module for human resource allocation and manufacturing resource planning for machine allocations are to be considered. For solving the unique hierarchy model, a shuffled frog leaping heuristic algorithm (SFLA) is proposed and implemented for minimizing the overall production cost. To prove the optimized results, the integrated system has been tested with real time case studies.

Design and structural analysis of 3D-printed modular furniture joints

Modular furniture joint defined as a connection used to connect two or more wood pieces to produce furniture with multiple functions. Notofusy furniture joint made from plywood was less expensive. However, during the manufacturing process, it was occasionally caused tear-out of wood fibre. Therefore, this research has been carried out to investigate and compare the existing material and Fused Deposition Modelling (FDM) fabrication method on the designed modular furniture joint. Finite Element Analysis (FEA) of elasto-plastic method from ABAQUS CAE software and three-point bending test were used to evaluate the structural analysis of designed modular furniture joint. In this research, the final concept selected was able to withstand load up to 730 kg and it only weights 113.59 g. The long-term goal for this research was to evaluate the possibility of producing end products using FDM technology. It was found that FDM contributed to cost effective in low volume production. In this research, the material focused were Acrylonitrile Butadiene Styrene (ABS) and Polyethylene Terephthalate (PETG). However, future studies can be conducted to evaluate the possibility of using other 3D printing materials.

A Review on metal 3D printing; 3D welding

3D printing is a well-known method to produce a 3D object and widely used in many types of industries including, mechanical, civil, medical, etc. The technology has been applied in industry for more than 20 years ago, but it is strictly limited to the slow production of small plastic objects, and some special fabric only. As its advancements, the technology of 3D printing becomes broad interest recently. In present industrial, 3D printers are able to produce high precision, quality products of different sizes fast at comparatively low cost. The aim of this paper is to highlight the importance of 3D printing in meeting low and medium production volumes besides having a review on metal 3D printing techniques available. The issue and challenges in producing metal 3D printing also will be discussed extensively in this paper. Suggestions on the subtractive method to complete the 3D printing process according to research interest also explained in this paper.

COMPETITIVENESS OF EXPORT AGRO PRODUCTS AND ECONOMIC POLICY FOR INCREASINGTHE COMPETITIVENESS

Agriculture plays a major role in ensuring the country›s food security, improving the balance of payments and strengthening state independence. Increasing the production of agricultural products increases the national income of the country, creates additional jobs and more. Competitive export production should play a major role in boosting agricultural production, as it has to be competitive in the international markets.The article analyzes the competitiveness of Georgian export agro products and the export-import of agro products. It should be noted that imports of primary agricultural products over the years have significantly outstripped exports, mainly due to the low volume of production of these products and the weak competitiveness of the sector relative to foreign producers. Competitiveness should be enhanced not by imposing barriers on imports, but by enhancing the competitiveness of locally produced products. That is why has been studied the main directions of economic policy for increasing the competitiveness by the example of Israel. Israel uses the theory and principles of knowledge-based economics to increase the innovation potential of the economy and enhance its competitiveness in general. In this study export agro products are identified by the following parameters: tendencies in export, stock reserves at the end of the year, resources, local production, average yield and self-provision coefficients. Thus, we assessed the competitiveness of corn/wine, nuts, potatoes, vegetables, wheat. Competitiveness level is calculated for selected Georgian agro products based on the received FAO data. The level of competitiveness of agro-food products was compared with each other on two markets: The European Union market (EU market) and the Commonwealth of Independent States market (CIS market). The product›s competitiveness level is calculated using the following indexes: Relative Export Advantage Index (RXA), Relative Import Penetration Index (RMP) and Relative Trade Advantage Index (RTA).The paper concludes that a high level of competitiveness in the international trade from Georgian agro products has nuts and wine. In addition, it is interesting that on CIS markets Georgian agro-food products have higher competitiveness than on the EU market. Also, on CIS markets competitive are potatoes and vegetables. Data analysis has shown that Georgian wine has far higher competitiveness on the CIS market than on the EU market. In recent years, the volume of Georgian wine exports to Russia has increased, which has been reflected in competitiveness indices. Consequently, the competitiveness of Georgian wine is increasing in the CIS market, while maintaining relative stability in the EU market. Also, Georgian nuts has far higher competitiveness on the EU market than on the CIS market. Conclusions are made according to the identified problems and the recommendations are offered on the directions of economic policies for increasing the competitiveness of agro-food products. It is important to identify agro-food products on the threshold of competitiveness in international trade in order to concentrate further resources and efforts on them, which will increase export volumes in the future. It is advisable to create a stable regulatory environment and increase the awareness of the Georgian agro-food product in international level.

Comparison of Conventional and Maskless Lithographic Techniques for More than Moore Post-Processing of Foundry CMOS Chips

This article details and compares the technology options for post–processing foundry produced CMOS at chip-scale to enable More than Moore functionality. In many cases there are attractions in using chip-based processing through the Multi-Project Wafer route that is frequently employed in research, early-stage development and low-volume production. This article identifies that spray-based photoresist deposition combined with optical maskless lithography demonstrates sufficient performance combined with low cost and operational convenience to offer an attractive alternative to conventional optical lithography, where spin-coated photoresist is exposed through a patterned photomask. [2020-0249]

Real-Time Decision-Support System for High-Mix Low-Volume Production Scheduling in Industry 4.0

Numerous organizations are striving to maximize the profit of their businesses by the effective implementation of competitive advantages including cost reduction, quick delivery, and unique high-quality products. Effective production-scheduling techniques are methods that many firms use to attain these competitive advantages. Implementing scheduling techniques in high-mix low-volume (HMLV) manufacturing industries, especially in Industry 4.0 environments, remains a challenge, as the properties of both parts and processes are dynamically changing. As a reaction to these challenges in HMLV Industry 4.0 manufacturing, a newly advanced and effective real-time production-scheduling decision-support system model was developed. The developed model was implemented with the use of robotic process automation (RPA), and it comprises a hybrid of different advanced scheduling techniques obtained as the result of analytical-hierarchy-process (AHP) analysis. The aim of this research was to develop a method to minimize the total production process time (total make span) by considering the results of risk analysis of HMLV manufacturing in Industry 4.0 environments. The new method is the combination of multi-broker (MB) optimization and a genetics algorithm (GA) that uses general key process indicators (KPIs) that are easy to measure in any kind of production. The new MB–GA method is compatible with industry 4.0 environments, so it is easy to implement. Furthermore, MB–GA deals with potential risk during production, so it can provide more accurate results. On the basis of survey results, 16% of the asked companies could easily use the new scheduling method, and 43.2% of the companies could use it after a little modification of production.

The fabrication of integrated and three-layer SU-8 nozzles for electrohydrodynamic printing

Electrohydrodynamic (EHD) jet printing can fabricate high resolution micro- and nano-scale lines with low cost and simple procedure. However, less attention has been paid to the fabrication of integrated nozzles with low cost and volume production capacity. In this work, three-layer SU-8 nozzles with slot dimension ranging from 10 to 50 μm were fabricated by ultraviolet photolithography and thermal bonding methods. The influence of the thicknesses (bottom and top layers) on the deformation of SU-8 nozzle was studied by numerical simulation. The results show that the suitable thicknesses should be 60 and 10 μm for bottom and top layer, to ensure the fabrication quality of SU-8 nozzles. Based on the established EHD printing platform, PEO (Polyethylene Oxide) lines with line-width from 750 nm to 8.2 μm can be printed by using the fabricated SU-8 nozzles, indicating the indicating the practicality of developed nozzle fabrication method.

Defect Probability Estimation for Hardness-Optimised Parts by Selective Laser Melting

The development of reliable additive manufacturing (AM) technologies to process metallic materials, e.g. selective laser melting (SLM), has allowed their adoption for manufacturing final components. To date, ensuring part quality and process control for low-volume AM productions is still critical because traditional statistical techniques are often not suitable. To this aim, extensive research has been carried out on the optimisation of material properties of SLM parts to prevent defects and guarantee part quality. Amongst all material properties, defects in surface hardness are of particular concern as they may result in an inadequate tribological and wear resistance behaviour. Despite this general interest, a major void still concerns the quantification of their extent in terms of probability of defects occurring during the process, although it is optimised. Considering these issues, this paper proposes a novel approach to quantify the probability of occurrence of defects in hardness-optimised parts by SLM. First, three process variables, i.e. laser power, scan speed and hatching distance, are studied considering their effect on hardness. Design of Experiments and Response Surface Methodology are exploited to achieve hardness optimisation by controlling process variables. Then, hardness defect probability is estimated by composing the uncertainty affecting both process variables and their relationship with the hardness. The overall procedure is applied to AlSi10Mg alloy, which is relevant for both aerospace and automotive applications. The approach this study proposes may be of assistance to inspection designers to effectively and efficiently set up quality inspections in early design phases of inspection planning.

이모티콘 관심도가 콜라보레이션 패션 상품 구매의도에 미치는 영향 - Preacher & Hayes의 매개효과 분석을 적용하여 -

Recently, the fashion industry collaborates with mobile messenger emoji to create fashion products. However, consumer behavior research on fashion collaboration with emoji is very limited. This study investigates female college students’ attitudes and purchases intentions toward fashion collaboration with emoji. SPSS 21.0 was used for the empirical analysis, and frequency analysis, multiple response analysis, exploratory factor analysis, reliability test, and mediation effect analysis using process macro by Preacher & Hayes were performed. The results show that there were fewer consumers who own fashion goods that collaborated with emoji than those who do not. Accessories were the most popular collaboration products. The present study showed that consumers’ interest in emoji directly affected consumers’ purchase intentions toward emoji collaborations, and consumers’ interest in emoji collaborations has a mediating role between interest in emoji and purchase intention toward emoji collaborations. Consumers’ interest in emoji has a direct effect on consumers’ intention to purchase fashion collaboration emojis when controlling interest in fashion collaboration emojis. In other words, the interest in emoji has a positive effect on the purchase intentions of fashion goods collaboration with emoji. Fashion collaborations with emoji help fashion brands form positive attitudes and brand image. For a newly established brand, collaboration with emoji will be effective brand advertising. Emoji collaborations will be used as a visual merchandising display technique and will be beneficial to fashion brands. Moreover, it will be effective for creating demand and exclusivity through low production volume.

Fabrication of Low-Cost Molds for Manufacturing of High Precise Micro Parts by Electroforming

In recent years, a broad range of microfabrication technologies have been developed for mass production. Manufacturing industry is however more and more facing the problem of producing personalized parts, resulting in low volume production. New technologies to allow economical fabrication of low volume micro-parts become a need. In this work, to address the issue of manufacturing high precise 3D micro-metallic parts for small series, 3D printing of micro-molds followed by electroforming to produce micro 3D metallic parts is proposed. This combination of processes can highly decrease fabrication costs for low volume production and allows to produce in parallel personalized parts.

3D PRINTER DESIGN, MANUFACTURING AND EFFECT OF INFILL PATTERNS ON MECHANICAL PROPERTlES

Along with the technological developments, it is an expected situation to discover new developed production methods. Additive manufacturing technologies, such as three-dimensional (3D) printers are one of these methods, allowing direct production of parts with complex geometries that cannot be produced by conventional methods. The most popular and inexpensive method among additive manufacturing technologies is FDM (Fused Deposition Modeling) method. This method is particularly interesting for the manufacture of parts with low production volumes.
 In this study, a 3D-FDM printer with a print volume of 200x200x210 mm has been designed and manufactured.PLA (polylactic acid) test samples having 2 different infill geometries were produced with the 3D printer. Tensile, three-point bending and charpyimpact tests were applied to these samples to investigate the effect of inner filling geometry on mechanical properties. The inner filling geometries are in the form of grid and gyroid. According to the results, while the geometry with the tensile force is "grid", while the geometry with the maximum bending force is "gyroid".It was concluded that different inner filling geometries do not have a significant impact on Charpy impact strength.

Challenges and opportunities to integrate the oldest and newest manufacturing processes: metal casting and additive manufacturing

Purpose This paper aims to investigate the current state, technological challenges, economic opportunities and future directions in the growing “indirect” hybrid manufacturing ecosystem, which integrates traditional metal casting with the production of tooling via additive manufacturing (AM) process including three-dimensional sand printing (3DSP) and printed wax patterns. Design/methodology/approach A survey was conducted among 100 participants from foundries and AM service providers across the USA to understand the current adoption of AM in metal casting as a function of engineering specifications, production demand, volume and cost metrics. In addition, current technological and logistical challenges that are encountered by the foundries are identified to gather insight into the future direction of this evolving supply chain. Findings One of the major findings from this study is that hard tooling costs (i.e. patterns/core boxes) are the greatest challenge in low volume production for foundries. Hence, AM and 3DSP offer the greatest cost-benefit for these low volume production runs as it does not require the need for hard tooling to produce much higher profit premium castings. It is evident that there are major opportunities for the casting supply chain to benefit from an advanced digital ecosystem that seamlessly integrates AM and 3DSP into foundry operations. The critical challenges for adoption of 3DSP in current foundry operations are categorized into as follows: capital cost of the equipment, which cannot be justified due to limited demand for 3DSP molds/cores by casting buyers, transportation of 3DSP molds and cores, access to 3DSP, limited knowledge of 3DSP, limitations in current design tools to integrate 3DSP design principles and long lead times to acquire 3DSP molds/cores. Practical implications Based on the findings of this study, indirect hybrid metal AM supply chains, i.e. 3DSP metal casting supply chains is proposed, as 3DSP replaces traditional mold-making in the sand casting process flow, no/limited additional costs and resources would be required for qualification and certification of the cast parts made from three-dimensional printed sand molds. Access to 3DSP resources can be addressed by establishing a robust 3DSP metal casting supply chain, which will also enable existing foundries to rapidly acquire new 3DSP-related knowledge. Originality/value This original survey from 100 small and medium enterprises including foundries and AM service providers suggests that establishing 3DSP hubs around original equipment manufacturers as a shared resource to produce molds and cores would be beneficial. This provides traditional foundries means to continue mass production of castings using existing hard tooling while integrating 3DSP for new complex low volume parts, replacement parts, legacy parts and prototyping.

Adopting a circular open-field layout in designing flexible manufacturing systems

ABSTRACT A new circular open field layout composed of a vehicle-based material handling system and multiple circular loops is proposed. The suggested layout offers more flexibility for high-mix low-volume production systems compared to other layouts as it maximizes the number of equidistant machines. A novel approach that integrates experimental design with computational modelling and statistical analysis was followed to study the proposed system. Forty experimental scenarios were generated using Face Centred Composite Design (FCCD) to numerically investigate the effect of layout, production quantity, variety and complexity on minimum production cost. To determine the minimum production cost in each experiment, a linear programming (LP) optimization model was formulated with layout dependent machine distance algorithm. The model solves for the optimum location of the machines and machine cell formations that minimizes the production cost. It considers material handling costs, alternative process routing, operations sequence, lot splitting, and machine costs. Furthermore, the cost was modeled using regression analysis to provide a quick estimate without the need to run computational intensive numerical models. Results reveal the effectiveness of the proposed layout with cost savings reaching 35% compared to traditional open field layout when product variety and complexity are increased.

Uncertainty evaluation in the prediction of defects and costs for quality inspection planning in low-volume productions

Quality-inspection strategies play a pivotal role in providing consumers with high-quality and defect-free products. In order to withstand the competition, organizations have an increasing interest in designing quality controls that are effective in detecting defects and economically viable. Recent studies have proposed a preliminary method to evaluate inspection effectiveness and cost in low-volume assembly processes, characterized by the production of single units or small-sized lots, even spread in long periods. Based on this method, the present paper aims to define a procedure to evaluate the robustness of defect and cost predictions in quality inspections of low-volume productions. The research questions which are specifically addressed concern how the uncertainty of models for defectiveness prediction can be assessed, and how this uncertainty may affect the selection of the most effective and affordable inspection strategy. The proposed approach allows to accurately analyze and compare different inspection strategies in terms of effectiveness and cost. First, the uncertainties of the statistical variables of the model for defectiveness prediction are evaluated by applying the law of combination of variances. Then, by combining the contributions of several inspection design parameters, the uncertainty is propagated to two indicators which quantify the overall effectiveness and cost of inspection strategies. In order to test the proposed methodology, a practical application concerning the assembly of mechanical components in an industrial manufacturing context is presented and discussed.

Multi-objective scheduling and assembly line balancing with resource constraint and cost uncertainty: A “box” set robust optimization

Assembly lines are flow-oriented production systems that are of great importance in the industrial production of standard, high-volume products and even more recently, they have become commonplace in producing low-volume custom products. The main goal of designers of these lines is to increase the efficiency of the system and therefore, the assembly line balancing to achieve an optimal system is one of the most important steps that have to be considered in the design of assembly lines. The purpose of the assembly line balancing is to assign tasks to the workstation called the station, so that prerequisite relationships, cycle times, and other assembly line constraints to be met and a number of line performance criteria to be optimized. In this study, considering the social responsibility related objective function, a mathematical model is proposed for scheduling and balancing the cost-oriented assembly line that has resource constraints with cost uncertainty. The box set robust optimization is applied and the obtained model is solved with the augmented epsilon constraint in the GAMS and some test problems and their results are presented. Finally, the cost parameter has been changed in a robust optimization approach and the obtained results have been analyzed for different costs.

Experimental study on single point incremental forming of Inconel 718

The contemporary sheet metal industry employs forming methods that use a precise die and punch to form components with precise tolerances. In mass production, the high cost of manufacturing dies and punches is absorbed by the number of components formed, whereas this is not the case for low volume production where it increases the manufacturing cost of the products. To overcome the demand for the development of manufacturing technologies that are both agile and meet industrial requirements, an incremental sheet metal forming experiment was carried out on Inconel 718. The incremental sheet metal forming process in the research stage needs to be improved both in terms of accuracy and product quality. The main process parameters involved in the study are incremental depth, rotational speed, and feed rate of the forming tool. Based on the process parameters, experiments are conducted using the Taguchi L9 orthogonal array design and responses such as geometrical accuracy, surface roughness, and thinning are studied. The forming limit and micro-structural study allow us to understand the forming behavior of Inconel 718, which will enhance the applicability of the material.

Heterodyne Eddy Current Testing Using Magnetoresistive Sensors for Additive Manufacturing Purposes

In recent years additive manufacturing technologies have become widely popular. For complex functional components or low volume production of workpieces, laser powder bed fusion can be used. High safety requirements, e.g. in the aerospace sector, demand extensive quality control. Therefore, offline non-destructive testing methods like computed tomography are used after manufacturing. Recently, for enhanced profitability and practicality online non-destructive testing methods, like optical tomography have been developed. This paper discusses the applicability of eddy current testing with magnetoresistive sensors for laser powder bed fusion parts. For this purpose, high spatial resolution giant magnetoresistance arrays are utilized for testing in combination with a single wire excitation coil. A heterodyne principle minimizes metrology efforts. This principle is compared to conventional signal processing in an eddy current testing setup using an aluminum test sample with artificial surface defects. To evaluate the influence of the powder used in the manufacturing process on eddy current testing and vice versa, a laser powder bed fusion mock-up made from stainless steel powder (316L) is used with artificial surface defects down to $100~\mu \text{m}$ . This laser powder bed fusion specimen was then examined using eddy current testing and the underlying principles.

Spatiotemporal constraints on the western Cauaburi Belt tectonics – northwestern Amazon Craton, Brazil

ABSTRACT The study of Precambrian tectonics is an intricate task, demanding a holistic approach to take an accurate view of geologic history. Here we attempt to set up the overview of an Orosirian-Statherian continental arc in the northwestern Amazon Craton, the Cauaburi Belt. Field relations, petrological, geochemical, and geochronological data of calc-alkaline metagranitoids, high-grade metasedimentary rocks, and peraluminous metasyenogranites yielded new interpretations about its tectonic evolution. The record of intense and episodic calc-alkaline magmatism between ca. 1805 and 1759 Ma, assign to the Cauaburi Complex, with field evidence of magma mixing and lodgement in a compressional tectonic regime, suggest a continental arc as the tectonic setting. During the magmatic lulls, deformation and metamorphism increase, culminating with the partial fusion of the high-grade metasedimentary rocks of the Taiuaçu-Cauera Complex. This succession composes the precursor paleobasin, presenting maximum and minimum depositional ages of 1819 and 1794 Ma, and was a relevant source for the calc-alkaline magmatism. The geochronological record of a low-volume production of peraluminous crustal rocks (Igarapé Tocandira Granite), with crystallization age at ca. 1791 Ma and metamorphic age at ca. 1771 Ma, also highlights the time and effect of the magmatic lulls. The Cauaburi Belt structural framework follows a general E-W to ENE-WSW trend, expressed in the Paleoproterozoic rocks as syn-magmatic and solid-state deformation fabrics. Assuming that Columbia Supercontinent nucleus assembled in the late Orosirian, we interpret that this coeval continental arc developed at its border and followed a north-south shortening direction, at current orientation.

Smart hardware integration with advanced robot programming technologies for efficient reconfiguration of robot workcells

The manufacturing industry is seeing an increase in demand for more custom-made, low-volume production. This type of production is rarely automated and is to a large extent still performed manually. To keep up with the competition and market demands, manufacturers will have to undertake the effort to automate such manufacturing processes. However, automating low-volume production is no small feat as the solution should be adaptable and future proof to unexpected changes in customers’ demands. In this paper, we propose a reconfigurable robot workcell aimed at automating low-volume production. The developed workcell can adapt to the changes in manufacturing processes by employing a number of passive, reconfigurable hardware elements, supported by the ROS-based, modular control software. To further facilitate and expedite the setup process, we integrated intuitive, user-friendly robot programming methods with the available hardware. The system was evaluated by implementing five production processes from different manufacturing industries.

Workload control in additive manufacturing shops where post-processing is a constraint: an assessment by simulation

Additive Manufacturing (AM) shops typically produce high variety, low volume products on a to-order basis. Products are first created in parallel batches at a single AM station before being subjected to several post-processing operations. While there exists an emerging literature on AM station scheduling and order book smoothing, this literature has largely neglected downstream post-processing operations, which also affect overall performance. Workload Control provides a unique production control solution for these post-processing operations, but the specific AM shop structure has been neglected in the literature. Using simulation, this study shows that load balancing via the use of workload norms, as is typical for Workload Control, becomes ineffective since the norm must allow for the operation throughput time at the AM station and for its variability. A sequencing rule for the jobs waiting to be released that inherently creates a mix of jobs that balances the workload is therefore identified as the best-performing rule. These findings reinforce the principle that load limiting should be used at upstream stations whereas sequencing should be applied at downstream stations. Finally, although the focus is on AM shops, the findings have implications for other shops with similar structures, e.g. in the steel and semi-conductor industries.