A systematic literature review

Integrated methodological frameworks for modelling agent-based advanced supply chain planning systems: A systematic literature review, The Supply Chain Management (SCM) paradigm is widely discussed today in virtually all industry sectors. A supply chain (SC) is a network of autonomous or semi-autonomous companies responsible for raw materials extraction, transformation into intermediary and finished products, as well as distribution and delivery to final consumers (Lee & Billington, 1993). These systems encompass several characteristics that render them quite intricate, according to the complexity’s theory.In order to cope with this complexity, modelling and simulation techniques are frequently used to understand these systems and to propose the best way to exploit them. For example, scientists and practitioners model and simulate supply chains to deal with problems related to: dynamic scheduling and shop floor job assignment, planning and scheduling integration problems, supply chain coordination problems, supply chain dynamics problems (Lee & Kim, 2008), information sharing, supply chain control structures, intelligent behaviour of supplychain members, evaluation of supply chain push and pull strategies, autonomy of supply chain partners and problem-solving algorithms and methods, among several other possibilities described in the literature.In an attempt to model and simulate these problems, many techniques have emerged since the 1950’s. Santa-Eulalia, D’Amours, Frayret and Azevedo (2009a) reviewed the state of the art of modelling and simulation techniques for capturing the complexity of supply chain systems. In this work, fourteen different modelling and simulation approaches were identified and organized into a novel taxonomy. One of the most pre-eminent categories identified is called multi-agent systems. Derived from Artificial Intelligence, this technique provides an innovative way to model and treat supply chain management problems.To extend this previous study, the objective of this paper is to review the literature related to agent-based systems for SCM. To do so, a new taxonomy classifying different methodological frameworks formodelling SCM problems was created. This taxonomy identifies that several dissimilar methods have been employed to represent agents in an SC since the 1990’s, as will be explained in the next subsection. The present work focuses on a specific category of this taxonomy which models “agent-based systems” to perform “advanced SC planning”. These agent-based systems are defined here as d-APS (distributed Advanced Planning and Scheduling systems), as proposed by Santa-Eulalia, Frayret and D’Amours (2008).Thesesystems represent an emergent domain, arising from the convergence of two fields of research. The first field deals with APS systems, proposing a centralized and hierarchical perspective of supply chain planning, generally treating a single company’s supply chain operations planning system. The second field concerns agent-based manufacturing technology, which entails the development of distributed software systems to support the management of production and distribution systems. APS systems employing agenttechnology (hereafter d-APS) propose mechanisms that overcome some of the limitations of traditional APS systems mainly related to: i) the inability to create sophisticated simulation scenarios (i.e. APS only proposes what-if analysis of part of the SC); and ii) the limitation in modelling distributed contexts to capture important business phenomena like negotiation and cooperation (Santa-Eulalia et al., 2008).In the domain of d-APS systems there is an important research gap (Govindu & Chinnam, 2010; Santa-Eulalia, Aït-Kadi, D’Amours, Frayret & Lemieux, 2011; Santa-Eulalia, 2009), which limits researchers in fully taking advantage o


Semantic process

What do information reuse and automated processing require in engineering design? Semantic process, Designing complex machines involves the creation of design sketches and blueprints of various types. In addition to the primary objective of documenting the machine design for purposes of implementationandproduction, the design information can be utilized also in other applications. These include simulations, technical documentation, and virtual laboratory applications for training purposes. According to the current practice, producing material that is not directly related to core machine design is often considered merely as a “secondary” objective. Further, the related secondary tasks are not always directly linked to the primary design activities with clear requirements. As a consequence, producing the artifacts related to the secondary applications is sometimes detached from the primary design process: It might be performed by different people with other tools, perhaps even re-engineering data (implicitly) present in the early design process. However, toreduce development costs, and to meet the needs of the other designers, the requirements and information flows between actors need to be acknowledged throughout the design process. Motivation for this is relatively clear: In an ideal case, many secondary applications, such as part catalogues and visualizations, could be programmatically generated from the original, rich enough design data.In this article, we present an information processing architecture that captures and reuses the flow of semantics-aware technical information in a design process from design information systems to the primary and secondary applications. Our main use case is semi-automatically generating virtual machine laboratories from existing design information, including simulations for virtual prototyping purposes. The main contribution lies in elaborating and explaining the underlying semantic process related to machine design. Compared with the state of the art, instead of insisting a central data repository or a toolset, we emphasize the information protocols between different design activities in design. This yields certain minimalism in process planning: It captures the critical information flow in a design process, but leaves room for design culture specific organization of individual design tasks and tools. Our work culminates into introducing a novel, semantic process model for analyzing and managing design information flows. This provides  an efficient method for reusing design information using semantic data processing pipelines. We also demonstrate this by generating a simulation model from design data, utilizing a library of general-purpose simulations blocks.While semantic modeling methods are increasingly adopted in managing design information structures, pipeline-orientedsemantic modeling is rather new. From our application point of view, semantic process perspective enables the low-cost semiautomatic generation of virtual machine libraries and other work products, secondary to traditional manufacturing. We also believe that the instructional aspect of this work very important, since it provides organizations conceptual tools for understanding and benchmarking their design processes, and promotes individual designer awareness (design as service vs. design as solo activity).We present our work in the context of a specific Semogen research project (phase I during 2010-2011) which studies industrial virtual laboratory production methods in the context of semantic modeling. Our applications are related to mobile rock-drilling machines with a human operator. The project is mainly funded by the Technology Industries of Finland Centennial Foundation and benefits from the expertise of its industrial partners of different domains, including design and manufacturing, CAD/CAM development, documentation, and engineer training. The rest of this article is organized as follows: After this Introduction, we outline the background of our work in Section 2. In Section 3, we consider the elements of well-defined and reusable design processes in general. In Section 4, we establish an abstract model for semantic data processing, and consider implementations. In Section 5, we present a case study of generating simulations from hydraulics diagrams, and discuss related experiences. Finally, in Section 6, we conclude the article and make notes about the related trends of engineering design.


Towards reducing traffic congestion

Towards reducing traffic congestion using cooperative adaptive cruise control on a freeway with a ramp, Building more roads and highways is no longer a feasible solution to reduce traffic congestion, a problem that has countless consequences. As expanding the infrastructure is often not practicable, due to the great expense and because most of the major traffic cities have already reached their maximum capacity for roads and highways, and with the ongoing advancement of artificial intelligence and wireless technology, the emphasis has turned to telematics technology integrated with Advanced Driver Assistance Systems (ADAS). The interest in ADAS applications has been expanding since the early nineties as a tool for making traffic more efficient and safer.ADAS technology functions by reducing (or supporting) the dependence on the human aspect in the driving task.Examples of such systems are: collision avoidance system, automatic parking, traffic sign recognition, driver drowsiness detection, lane departure warning system, and blind spot detection.Adaptive Cruise Control (ACC) is an ADAS system introduced by General Motors in 1990 that issimilar to conventional cruise control in that it attempts to maintain the cruise speed initially set by the driver in the addition of the equipped vehicle maintaining a proper safe distance with the predecessor vehicle. As shown in (figure 1), using a forward-looking radar (or laser/Lidar setup) installed behind the front grill of the vehicle, the ACC equipped vehicle (the vehicle on the right in this case) has the ability of detecting the speed and distance of the predecessor vehicle or any other obstacle ahead. Thus, if the predecessor vehicle decelerates, the braking system of the ACC vehicle is signaled to decelerate. If the predecessor vehicle accelerates again, the engine is signaled to accelerate, limited by the initial cruise control maximum desired speed set initially by the driver ACC system has several operational disadvantages. For instance, an ACC equipped vehicle has a limited deceleration range and its ACC system cannot be used at very high or low speeds (Aremet al., 2003).With a constant demand for traffic information on the surrounding traffic conditions and with the recent developments of vehicle-to-vehicle communication via Vehicular Ad-hoc Networks (VANETs), a recent potential of vehicles sharing traffic information to tackle traffic congestion and impact the traffic dynamics positively started to appear. Wireless communication via VANETs has been adopted due to the great advantages offered by the technology allowing high mobility, efficiency, and also being economically feasible. Cooperative Adaptive Cruise Control (CACC) is a more advanced technology providing the equipped vehicles with more accurate information about the preceding vehicle through speedy and real-time vehicle-to-vehicle traffic data sharing among CACC equipped vehicles. The effect of CACC on the traffic flow and safety is still vague due to the deficiency of research in this area.Therefore, this research was oriented towards intelligent transportation systems (ITS) and particularly focused on CACC systems, and their effect on traffic dynamics.The latter’s growing popularity is still premature.Most of the CACC related literature defines designs and frameworks of the CACC technology, but fail to focus on the overall impact of CACC systems on the traffic characteristics (Arnaout & Bowling,2010).In order to address this topic, the CACC systems have to be explored thoroughly by studying how the drivers use the systems, how the equipped vehicles communicate


Designing and implementation of an IMF

Designing and implementation of an IMF (intelligent manufacturing system), Global competition and rapidly changing customer requirements are forcing major changes in the production styles and configuration of manufacturing organizations. Increasingly, traditional centralized and sequential manufacturing process planning, scheduling, and control mechanisms are being found insufficiently flexible to respond to changing production styles and high-mix low-volume production environments (Shenet al., 1999). The traditional approaches limit the expandability and reconfigurability of the manufacturing systems (Sanchez& Nagly, 2001). The centralized hierarchical organization may also result in much of the system being shut down by a single point of failure, as well as plan fragility and increased responseoverheads (Yang& Xue, 2003). In the last twenty years manufacturing concepts have had several redefinitions. In the eighties, the concept of flexible manufacturing systems (FMC) was introduced to develop a new family of products with similar dimensions and constraints, but nowadays, the capacity of reconfiguration has become a major issue for improving the functioning of industrial processes (Revillaet al., 2008). Indeed, today a main objective is to adapt quickly in order to start a new production or toreact in a failure occurrence. Intelligent manufacturing systems (IMS) offer not only both flexibility and reconfigurability, but also this concept brings more than a few ideas of software intelligence meanings, which contemplated characteristics such as autonomy, decentralization, flexibility, reliability, efficiency, learning, and self-regeneration (Revillaet al., 2008; Mekidet al., 2009; Shenet al., 2006).The current challenge is to develop collaborative and reconfigurable manufacturing control systems that support efficiently small batches, product diversity, high quality and low costs, by introducing innovative characteristics of adaptation, agility and modularization. Information and communication technologies, and artificial intelligence techniques, have been used for more than two decades addressing this challenge. Namely, agent-based and Holonic manufacturing control seem to be suitable to face these requirements such as modularity, scalability, autonomy and re-usability, since they present decentralization of control over distributed structures. When properly designed and implemented, agent-based control systems result in a performance that is flexible, robust, adaptive and fully tolerant, which are key factors for manufacturing success in the increasingly global marketplace (Aized, 2010).Recently, there has been growing interest in the holonic approach to the development of complex industrial and business systems. Motivated by the need to enable these man-made systems to adapt to disturbances while maintaining system stability and efficient use of resources, Holonic systems were inspired by Arhtur Koestler’s early observations of the structure and behavior of living organisms and social organizations (Koestler, 1967). Like multi-agent systems (MAS), holonic systems are composed of self-reliant units that are capable of flexible behavior. More specifically though, a holon can be thought of as a special type of agent that is characteristically autonomous, cooperative and recursive, that populates asystem where there is no high-level distinction between hardware and software. Although both approaches share many basic concepts, research in each area has been conducted independently for the most part. Holonic systems research has primarily focused on intelligent manufacturing systems and has been organized around the international Holonic Manufacturing Systems (HMS) consortium (Cheng et al., 2004). In contrast, MAS research is much broader in scope, focusing generally on the development of systems in which “data, control, expertise or resources are distributed; agents provide a natural metaphor for delivering system functionality; or a number of legacy systems must be made to interwork” (Leitão, 2009).The manufacturing enterprises of the 21st century are in an environment where markets are frequently shifting, new technologies are continuously emerging, and competition is globally increasing. Manufacturing strategies should therefore shift to support global competitiveness, new product innovation and customization, and rapid market responsiveness (Prajogoet al., 2007). The next generation manufacturing systems will thus be more strongly time-oriented (or highly responsive), while still focusing on cost and quality. Such manufacturing systems will need tosatisfy a number of fundamental requirements, including (Shenet al., 2006; Chituc& Restive, 2009):Full integration of heterogeneous software and hardware systems within an enterprise, a virtual enterprise, or across a supply chainOpen system architecture to accommodate new subsystems (software or hardware) or dismantle existing subsystems “on the fly”Efficient and effective communication and cooperation among departments within an enterprise and among enterprisesEmbodiment of human factors into manufacturing systemsQuick response to external order changes and unexpected disturbances from both internal and external manufacturing environmentsFull tolerance both at the system level and at the subsystem level so as to detect and recover from system failures and minimize their impacts on the workflow environment


Perawatan Preventif Untuk Peralatan Mesin CNC

Perawatan Mesin CNC

Perawatan Preventif Untuk Peralatan Mesin CNC  .Di masa-masa sulit seperti ini, produsen dan pembuat komponen seperti Anda perlu meregangkan dana investasi peralatan Anda. Untuk menjaga fasilitas produksi Anda tetap berjalan, diperlukan program pemeliharaan preventif yang sistematis dan terkalibrasi untuk peralatan mesin CNC Anda seperti mesin bubut CNC dan pusat pemesinan. Ini akan memastikan bahwa peralatan Anda terus berfungsi dengan baik meskipun sering digunakan dan dalam waktu lama.

Dalam artikel ini, Anda akan mempelajari beberapa praktik terbaik dalam memeriksa, memelihara, dan membersihkan peralatan mesin CNC Anda agar tetap dalam kondisi optimal bertahun-tahun setelah dipasang di lantai toko Anda.

Mengapa Perawatan Alat Mesin CNC Dibutuhkan?

Perkakas mesin CNC bukan hanya alat tugas berat yang tahan lama – alat ini juga harus sangat akurat untuk unggul dalam peran pemesinannya di lantai pabrik Anda.

Peralatan mesin seperti mesin bubut, mesin milling, dan pusat permesinan multi-sumbu sering kali melakukan banyak tugas pemesinan. Banyak dari tugas pemotongan, pembentukan, dan pengeboran ini sangat rumit, dan memerlukan perangkat lunak dan perangkat keras yang dirancang khusus untuk dijalankan. Mereka membutuhkan periode produksi yang panjang dan tidak terputus untuk menyesuaikan dengan kebutuhan unik manufaktur pabrik – seringkali berlangsung selama siang dan malam.

Perawatan Mesin CNC

Karena tingkat kinerja yang tinggi dan waktu pengoperasian serta pemotongan yang lama yang diperlukan untuk berbagai suku cadang dan komponen logam, diperlukan perawatan rutin dan preventif. Ini akan membantu perkakas mesin CNC Anda bertahan lebih lama, tetap dapat diservis untuk jangka waktu yang lebih lama, sambil menjaga akurasi dan kualitas suku cadang mesin Anda.

Manfaat Perawatan Reguler Untuk Peralatan Mesin CNC

Apakah ada manfaatnya menggabungkan program pemeliharaan preventif dan rutin untuk peralatan mesin Anda?

Izinkan kami mencantumkan beberapa di antaranya untuk Anda:

1.  Membantu untuk terus meningkatkan profitabilitas perusahaan Anda

2.  Mencegah dan mengurangi waktu henti mesin dan produksi

3.  Tingkatkan dan pertahankan produktivitas alat mesin

4.  Perpanjang umur mesin dan alat pemotong Anda

5.  Meminimalkan atau menghilangkan tabrakan atau kecelakaan yang dapat membahayakan operator

6.  Tingkatkan efisiensi dengan menggunakan lebih sedikit bahan dan mengurangi bahan bekas

7.  Kurangi dan hindari biaya perbaikan yang besar dan besar dari kerusakan tak terduga pada mesin Anda

Sekarang setelah Anda mempelajari manfaatnya, mari kita lihat langkah-langkah yang Anda butuhkan untuk menjaga peralatan mesin Anda dalam kondisi kerja prima.

Daftar Periksa Perawatan Preventif Harian / Mingguan untuk Peralatan Mesin

Sebagian besar pemeriksaan pencegahan dan pemeliharaan harian dan mingguan dilakukan oleh operator mesin Anda.

Prosedur perawatan rutin ini diperlukan untuk memastikan bahwa laju produksi Anda tidak diperlambat oleh kesalahan sederhana seperti berikut ini:

1.  Menghentikan mesin karena gagal mengisi ulang oli pelumas (atau lebih buruk lagi, stok oli tidak mencukupi)

2.  Penyumbatan produksi karena chip – terutama chip aluminium – tidak dibersihkan, sehingga chip meluap

3.  Pasokan udara yang buruk (volume dan kualitas), yang dapat mengakibatkan kerusakan yang merugikan. Udara yang kotor atau lembab dapat mempengaruhi kualitas produksi.

4.  Penurunan level pendingin di bawah batas, mengakibatkan panas berlebih dan kerusakan Daripada menyalahkan produsen, Anda harus membuat program perawatan dan pemeliharaan harian atau mingguan yang sederhana.

Berikut beberapa langkah yang dapat Anda atau operator Anda lakukan:

  • Periksa level cairan pendingin Periksa alat pemotong di ATC Periksa sistem hidrolik apakah ada kebocoran
  • Periksa pasokan udara untuk memastikannya bersih dan kering Periksa kebocoran atau suara aneh Lumasi bagian mesin yang bergerak Pastikan spindle, chuck, dan bagian yang bergerak dibersihkan dengan sikat atau dibilas dengan cairan pendingin.
  • Pastikan spindle, chuck, dan bagian yang bergerak dibersihkan dengan sikat atau dibilas dengan cairan pendingin. Periksa pompa dan chuck pneumatik.
  • Catatan: Ini sangat penting karena chuck yang dioperasikan dengan pneumatik sangat sensitif, dan bekerja paling baik jika dirawat secara teratur. Kerusakan pada penyegelan dan kurangnya pelumasan bisa sangat mahal untuk diperbaiki.
  • Pastikan chip dibersihkan tetapi tidak tertiup angin untuk mencegah kerusakan.
  • Catatan: Untuk mesin CNC, pembersihan serpihan, kotoran atau pendingin tidak boleh dilakukan dengan meniupnya menggunakan senapan angin. Ini karena air-gun dapat mendorong chip dan pendingin di area di mana produsen mesin benar-benar berupaya mencegahnya mencapai (menggunakan penutup mahal dengan wiper misalnya).

Daftar Periksa Perawatan Triwulanan / Semi-Tahunan Untuk Peralatan Mesin

Setiap tiga bulan atau enam bulan sekali, periksa apakah tangki pendingin, reservoir udara, pompa, dan drainase oli Anda berfungsi dengan lancar. Anda dapat melakukannya dengan memastikannya bersih dan bebas pengoperasian.

Misalnya, tangki pendingin Anda dapat mengumpulkan lumpur dari waktu ke waktu jika tidak dibersihkan secara teratur. Seiring waktu, hal ini tidak hanya mengurangi keseluruhan kapasitas tangki Anda untuk pendingin – ini juga dapat memengaruhi kemurnian cairan pendingin Anda dan merusak kinerja spindel Anda. Ini sangat merusak jika sistem CTS (Coolant Through Spindle) digunakan. Keripik dan partikel halus akan tersedot melalui Pompa CTS Anda, merusaknya pada waktunya. Penahan alat mesin dan kerucut spindel Anda juga dapat rusak.

Untuk mencegah kecelakaan seperti itu terjadi, lakukan hal berikut setiap triwulan atau setengah tahunan:

  • Minta tangki pendingin dibersihkan dari lumpur, keripik, dan oli
  • Copot chuck dan rahang dari mesin dan bersihkan
  • Periksa leveling mesin Anda dan sesuaikan jika perlu
  • Bersihkan radiator sambil memastikan sirip radiator lurus dan tidak rusak
  • Periksalah semua wiper dari segala kerusakan – bersihkan dan ganti wiper yang rusak Biarkan tangki hidrolik dikosongkan, dan ganti oli hidrolik dengan oli hidrolik baru. Pastikan juga bahwa filter garis dan filter hisap diganti.
  • Biarkan unit pelumasan dikeringkan dan dibersihkan – setelah itu Anda harus menambahkan pelumas baru
  • Jika mesin Anda dilengkapi dengan unit pendingin, biarkan unit pendingin dikeringkan dan diisi ulang

Daftar Periksa Perawatan Tahunan Untuk Peralatan Mesin

Bagaimana dengan jadwal perawatan tahunan Anda? Bagaimana Anda menjaga peralatan mesin Anda dalam kondisi prima dari tahun ke tahun?

Pertama, Anda perlu mencatat bahwa semakin banyak sumbu yang dimiliki Alat Mesin CNC Anda (seperti Pusat Pemesinan 5 sumbu), semakin penting untuk menjaganya tetap sejajar dan dikalibrasi. Untuk peralatan mesin yang begitu rumit, Anda perlu memeriksa status alas mesin, sistem hidrolik, dan sistem pelumasan spindel Anda. Anda juga harus menguji untuk memastikan bahwa akurasi peralatan mesin dan tingkat peralatan mesin Anda dapat memenuhi kebutuhan Anda.

Berikut adalah beberapa hal yang harus dilakukan untuk peralatan mesin Anda setiap tahun:

  • Minta spindel untuk memeriksa masalah pemutaran radial dan ujung
  • Periksa apakah silinder chuck sudah habis
  • Periksa tailstock untuk ketidaksejajaran dan fungsi pena bulu
  • Periksalah paralelisme dan kemiringan turret
  • Minta seluruh mesin memeriksa kebocoran oli atau udara
  • Periksa apakah headstock ada kerusakan atau ketidaksejajaran, dan spindle taper di mesin milling
  • Minta distributor / pemasok Anda memeriksa gib sumbu X, Y dan Z dan menyesuaikan jika perlu. Periksa dengan cara yang sama fungsi tabel sumbu ke-4 Anda
  • Minta distributor / pemasok Anda menjalankan program serangan balik untuk memeriksa serangan balik di sumbu X, Y dan Z dan sesuaikan jika perlu

Setiap tahun, disarankan untuk melakukan pemeriksaan mesin CNC secara keseluruhan sehubungan dengan leveling, akurasi, dan fungsionalitas. Ini harus dilakukan oleh teknisi servis produsen mesin atau setidaknya oleh teknisi dealer yang terlatih dan bersertifikat pabrik. Para profesional yang berkualifikasi ini akan tahu apa yang harus dilakukan dan apa yang harus diwaspadai – mereka juga akan memiliki peralatan untuk melakukan pekerjaan dengan benar.


Seperti kata pepatah, mencegah lebih baik daripada mengobati. Sama seperti tubuh manusia, menjaga peralatan mesin CNC Anda dalam keadaan baik akan memastikan keawetan, keakuratan, dan penggunaan produktifnya dalam jangka panjang.

Dengan demikian, menggabungkan jadwal perawatan rutin adalah suatu keharusan untuk lantai bengkel yang menggunakan mesin CNC untuk proses produksinya.

Selain menjaga mesin Anda agar berjalan dengan baik, penting untuk berinvestasi pada peralatan mesin CNC berkualitas tinggi yang mudah dirawat, dan yang dilengkapi dengan dukungan purna jual yang baik.

Peralatan mesin Hwacheon dibuat dengan desain mekanis yang kaku, berkualitas tinggi, dan tahan lama. Namun, seperti halnya tubuh berharga Anda, Anda memerlukan program perawatan dan perawatan rutin agar tetap berjalan optimal untuk waktu yang lama.

Untuk mempelajari lebih lanjut tentang paket layanan Hwacheon dan bagaimana kami melakukan pemeliharaan preventif, hubungi kami untuk informasi lebih lanjut atau untuk mendapatkan penawaran.


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