Information flow in model of e-production systems

Pełen tekst

(1)INFORMATION FLOW IN MODEL OF E-PRODUCTION SYSTEMS ANDRZEJ JARDZIOCH, JDRZEJ JASKOWSKI. Summary Manufacturing processes are becoming increasingly automated. Introduction of innovative solutions often requires the processing of multiple signals from various devices. Correctness tests of the components’ configuration become a complicated operation, requiring vast expenditures of time and knowledge. Every simple manufacturing system involves many different signals from any machine. A correct and simple connection between units is now being provided with industrial automatic standards like Ethernet, Modbus, Profibus, Can, Ethernet Powerlink and many more. Choosing the best protocol is an important decision. A properly prepared information flow diagram is very helpful in making the right decision. This paper shows the building of an information flow model based on a fully-automated manufacturing system. As a result, suggested connections between modules were shown. Keywords: e-Production, simulation, model, information flow, manufacturing 1. Introduction In today's world, competition is not possible without addressing issues of globalization and the comprehensive use of IT tools. Even 10 years ago, we vastly underestimated the Internet's potential to reach more clients and business partners. However, by 2007 over 2 billion people worldwide had already used the Internet to access goods and services, and Internet strategies had become an integral part of business models of a large part of the world economy. One of the rapidly growing methods of integrating the Internet into business operations has become the eSCM (e-Supply Chain Management) [6, 7]. Small and medium-sized companies are often asked to fulfil orders for small amounts or variable types of products. These products often have technologically complicated components, the manufacturing of which may require specialized machinery that these small companies may not have. The small volume of an order makes purchasing specialized machinery uneconomical; so the only way out may be to outsource the manufacturing of this component elsewhere, using the Internet to locate the required hardware and production capacity [1, 4]. This Internet-enabled outsourcing is part of a wider process we would like to call e-Production. In short, e-Production is manufacturing commissioned and programed via the Internet. It relies on fully-automated machines, robotized and maintenance-free. E-Production can be carried out regardless of the distance between the client and producer. The benefits of e-Production for small and medium-sized companies lie in the access to advanced technology they would not otherwise.

(2) 84. Jardzioch Andrzej, Jaskowski JĊdrzej Information flow in model of e-Production systems. have, while the benefit for large companies with advanced technologies lies in the ability to take better advantage of that technology by securing more orders and increasing their market-share. Technological and economic performance of an enterprise can be often improved by simulation and modelling. Simulation is one of the most important techniques supporting production management [5, 8]. The market forces companies to solve increasingly complex problems in the shortest possible time. Modelling of manufacturing systems aims at understanding the structure and operation of constructed facilities. Models can be real or virtual (e.g., a computer model). They are necessary because the industrial equipment or even consumer products are becoming increasingly complex. In most cases, multiple models are created, each presenting a different approach towards the same or different parts of the system [3, 10]. Modelling and simulation are widely used in many industries. Due to strong competition in the global markets, manufacturing companies cannot afford even the slightest error or delay in production. Such errors can result in increased production costs, as well as significant losses. In the traditional process of design and analysis of automated manufacturing systems a large number of variants of possible solutions exist, which makes selection of the best solution difficult. The matter may be further complicated by short decision time allowed for the change in production schedule. In both cases, the results of simulation studies prove useful, offering dynamic production scheduling [2, 9]. This paper consists of 7 chapters. The first chapter is an introduction reviewing the literature. Chapter 2 shows features of a traditional manufacturing system. The third chapter presents the idea of e-Production. Subsection 3.1 draws attention to the specific features of water-jet cutting. It is important because cutting a surface is the easiest of all possible treatments, but there are still a lot of problems to solve. Chapter 4 describes the proposed management algorithm. Chapter 5 shows technical requirements. It presents current technology solutions. Chapter 6 shows modules of eProduction. The last chapter – chapter 7 describes information flow between modules. 2. Traditional manufacturing In traditional manufacturing, a customer has to come in person to the facility. After a meeting with a salesperson, a production engineer and maybe some more people, the customer knows the price and approximate date of delivery. That is the customer’s point of view. From the manufacturer’s side it looks differently. First, the salesmen analyse the order and compare it with similar projects that were completed. Then they calculate the time for order delivery. At that point, the production engineer joins the project. He develops technologies for the manufacturing process. Following that, the project manager can calculate the time, number of workers and amount of material. Next the information goes back to the salesman, who calculates price and firms up the delivery date; he also communicates with the customer to set the details. A simple information flow of traditional manufacturing system is shown in Figure 1. 3. The concept of flexible manufacturing system, working under the condition of Internetreleased production capacity The concept of releasing production capacity through the Internet allows the production sphere to become public. Manufacturing processes that uses the Internet could fall into several groups: - e-Design – Internet-aided, team work in order to accelerate work on a product,.

(3) 85. Studies & Proceedings of Polish Association for Knowledge Management No. 60, 2012. -. e-Planning – Internet-aided planning of a production process, e-Supply – Internet-aided material supply, e-Manufacturing – automated manufacturing by using the Internet to acquire new orders.. Material Warehouse . . Project Manager. . 3URGXFWLRQ . Production Engineer. Workers. Figure 1. Information flow in traditional manufacturing Source: own elaboration. Figure 2 illustrates the idea of e-Production on a hypothetical example. There are 3 types of production processes in this case: - Cutting flat surface (a metal sheet) with a number of possible technologies (plasma, laser, water-jet). This is the simplest alternative with the least difficulty of processing and configuration of CNC parameters. - Turning on the CNC multi-tool lathe. This option features a medium degree of difficulty of processing and configuration of the CNC parameter. - Milling using the CNC multi-tool centre. This is the most complicated option and poses a maximum degree of difficulty of processing and configuration CNC parameters. The presented scheme does not show an option when a product needs to be worked on more than one machine. The situation when a product is subject to multi-machining is the most complicated. Production starts when a client places his/her order on e-Production website. Entered data is then analysed by an automatic management system. This system analyses the date, material, shape and material condition. It then provides a response to the customer, giving the estimated date of completion and price. Now the customer can choose between accepting the conditions and changing the parameters of the order. After acceptance, the management system uses an advanced planning algorithm. After cutting, cut elements are subject to quality control. The remaining material is dealt with in one of two ways: if there is still enough material left for further use, the material is transferred back to sheet depot; otherwise it is moved to a waste room..

(4) 86. Jardzioch Andrzej, Jaskowski JĊdrzej Information flow in model of e-Production systems. Customer. . Customer. - . !. e-Production. control. management system. Water jet. CNC. "#. On-line system. CNC Mill. Lathe. Robot. Robot. Robot. Automatic Sheet. Automatic Sheet. Automatic Sheet. depot. depot. depot. Quality control. Figure 2. Idea of e-Production Source: own elaboration..

(5) 87. Studies & Proceedings of Polish Association for Knowledge Management No. 60, 2012. 3.1. Water Jet work specification Water-jet is a technology of cutting that uses high-pressure water and sand. This method allows for the cutting of materials such as steel, stone, glass, composite, polymer, wood, aluminium and many others. The cut side has a very good surface and there is no risk of overheating material. The simplest water-jets have 3 axes and work similar to a plotter. Advanced machines have 5 axes and can cut more shapes with better accuracy. This project research focuses on a 3-axis machine. Cutting speed depends on material, thickness and quality. There are tables that show the optimal parameters of cutting speed, pressure and amount of sand. An automatic system can choose parameters from that table or a Fuzzy-Logic algorithm could be implemented. The use of an artificial algorithm could be a better option in the case of a customized material. There are many different algorithms with different effects on planning. Choosing only one is not possible. This problem is much greater when more than one object and more different shapes are involved. Optimization of nesting remains the subject of many studies. 4. Advanced management algorithm Management is the most important function in e-Production. Properly built algorithms determine optimal work of the entire system. In fully-automated manufacturing, the management subsystem has to make decisions that used to be made by many people. Before a human made a decision, he considered many options. To choose the best option he used his knowledge, experience and many other variables. An algorithm, which could replace a human, has to operate on similar principles. There has to be some feedback from other subsystems, which is shown in Figure 3.. Figure 3. Feedback in management algorithm Source: own elaboration..

(6) 88. Jardzioch Andrzej, Jaskowski JĊdrzej Information flow in model of e-Production systems. Proper connection orders require a rule. This rule tells when a connection is possible and when it is not. The first step is to check the type of material. If orders have the same material, they probably will be connected. Most nesting algorithms use a condition to minimize waste, but there are some more parameters of the order that will be more important. Figure 4 shows a variation of the 3 most logical parameters.. Figure 4. Important parameters to connect orders Source: own elaboration. Because of a situation when more than one pair of orders can be connected to one another, more than one parameter has to be used. For example, the first step is to check if the material is the same, then (using FIFO principle) to check the date of acceptance (if there are still too many orders with the same priority), next can be the due date and finally profit. Which way of this diagram is better is still a point of research. The traditional way aims at minimising the delay of orders. 5. Hardware requirements All information flow depends on the method of connection between machines, sheet depot, robot, management system and server. Most modern PLCs can send a lot of information to the main production server. There is also a possibility of remotely changing settings on the PLC. Most PLCs are simple logic controllers, but leaders of automation offer advanced PAC controllers. These controllers can be connected straight to the Ethernet. To simplify connections between different producers, international standard PLC Open was developed. “It harmonizes the way people design and operate industrial controls by standardizing the programming interface. A standard programming interface allows people with different backgrounds and skills to create different elements of a program during different stages of the software lifecycle: specification, design, implementation, testing, installation and maintenance. Yet all the pieces adhere to a common structure and work together harmoniously. The standard includes the definition of the.

(7) 89. Studies & Proceedings of Polish Association for Knowledge Management No. 60, 2012. Sequential Function Chart (SFC) language used to structure the internal organization of a program, and four inter-operable programming languages: Instruction List (IL), Ladder Diagram (LD), Function Block Diagram (FBD) and Structured Text (ST). Via decomposition into logical elements, modularization and modern software techniques each program is structured, increasing its re-usability, reducing errors and increasing programming and user efficiency. Based on application requirements and project specifications engineers are required to use or select a wide range of motion control hardware. In the past this required unique software to be created for each application, although the functions are the same. PLC open motion standard provides a way to have standard application libraries that are reusable for multiple hardware platforms. This reduces development, maintenance, and support costs while eliminating confusion. In addition, engineering becomes easier, training costs decrease, and the software is reusable across platforms. Effectively, this standardization is done by defining libraries of reusable components. In this way the programming is less hardware-dependent, the reusability of the application software is increased, the cost involved in training and support is reduced, and the application becomes scalable across different control solutions. Due to the data hiding and encapsulation, it is usable on different architectures: for instance, ranging from centralized to distributed or integrated to networked control. It is not specifically designed for one application, but it will serve as a basic layer for on-going definitions in different areas. As such, it is open to existing and future technologies.” [7]. Figure 5. Connection between components of e-Production Source: own elaboration..

(8) 90. Jardzioch Andrzej, Jaskowski JĊdrzej Information flow in model of e-Production systems. Another important standard is OPC (OLE for process control). “OPC is a series of standards specifications. The first standard (originally called simply the ‘OPC Specification’ and now called the ‘Data Access Specification’) resulted from the collaboration of a number of leading worldwide automation suppliers working in cooperation with Microsoft. Originally based on Microsoft's OLE COM (component object model) and DCOM (distributed component object model) technologies, the specification defined a standard set of objects, interfaces and methods for use in process control and manufacturing automation applications to facilitate interoperability. The COM/DCOM technologies provided the framework for software products to be developed. Current and emerging OPC Specifications include: OPC Data Access, OPC Alarms & Events, OPC Batch, OPC Data eXchange, OPC Historical Data Access, OPC Security, OPC XML-DA, OPC Complex Data and OPC Commands. [8] When all machines and PLCs are modern enough, connections might be like Figure 5. 6. Modules of e-Production E-production is an advanced system consisting of many independent modules. The most important module is management that includes: - Communication module which contacts with customer and outside service; - Verification module, checks correctness parameters of order; - Estimation module, estimates due date and price; - Stock module, orders material, manages material that is returned to the sheet depot after cutting; - Scheduling module, choses optimal algorithm to planning production; - Report module, generates quality reports; - Service module, calls for service if something wrong happened, watches machines status; - Simulation module – makes a simulation of a process for every possible scheduling. Module for nesting. To minimize the waste there are some possible cutting methods. This module also has to plan cutting on material that is not new. This is a more difficult problem. There could be more than one used sheet and the module has to choose which sheet fits better for the order or connected orders. Finally, this module generates the final shape for cutting and for manipulating a robot. Module for robot. This module generates control program to pick up cut elements. It analyses the shape of elements and chooses the right grab. Most grabs for that kind of material are made of a vacuum cup or an electromagnet. To minimize the maximum range of different grabs there is an idea to use one big grab with many vacuum cups. After shape analysis, the algorithm chooses which cups will be active and which will not. The grab could take most possible shapes except the shapes with many holes where the free surface is smaller than the diameter of a vacuum cup. The shape like a spider web is extremely hard to grab. To grab something like this, a robot has to pick up a whole sheet of material. To manage this, a special grab that looks like a comb was developed. Before the robot uses the grab, it has to clear a water jet table of any waste. Module for sheet depot. This module controls the high-storage sheet depot. It generates programs for the sheet stacker, chooses a suitable shelf for returning material and sorting returned sheets. Because of different kinds and conditions of material, there are some options of work.

(9) 91. Studies & Proceedings of Polish Association for Knowledge Management No. 60, 2012. available. Figure 6 presents seven different possibilities. The most effective use of space is option IV but it is the most complicated. Option I was chosen for the project analysed.. Figure 6. Possible options of sheet depot work Source: own elaboration. Module for quality control. This module compares an original drawing delivered by a customer and the picture of cut elements taken by an industrial camera. After making a comparison, it generates a report. Module for water-jet. This module generates a control program. It can also conduct a fast simulation of cutting to calculate the time. This module is an independent program to find optimal cutting parameters. As mentioned before, the fuzzy logic algorithm could be suitable for this. 7. Information flow E-Production is not a simple system with a straight information flow. There are some feedbacks between modules, which also have many connections to one another. The heart of the system is the management module. The module concentrates information from every module. If it wants to develop a diagram of information flow between modules, this diagram could look like Figure 7. Every connection is a package of information. If one wanted to show the full spectrum of information, this diagram will be much bigger and probably difficult to read. Figure 7 illustrates the information in e-Production system. The diagram contains 7 basic modules: communication (1), verification (2), stock (3), estimation (4), service (5), scheduling (6), simulation (7) and report (8). Modules 9–12 are responsible for the operation of all the technological devices (water jet, robot, sheet depot, quality control station). Module 13 contains nesting algorithms. Module 14 is an order database. Module 1 is an interface between the outside world and the e-Production system. When an order arrives, this module sends basic parameters to the verification (2) module. Now module 2.

(10) 92. Jardzioch Andrzej, Jaskowski JĊdrzej Information flow in model of e-Production systems. checks the entered data to see if it is correct. If everything is good, the order goes to the estimation module (3). In this module, the artificial intelligence algorithm predicts an end date and price. These results return to the first module and will be sent to a client. After the client’s acceptance, the order is sent to the scheduling module (6). This starts the scheduling process. The system chooses orders with the same material and sends them to the nesting module (13).. Figure 7. Information connections in e-Production system Source: own elaboration. Returned “packages” of orders are lined up and sent to the simulation (7), robot (10) and water jet (9) modules. Numbers 10 and 9 calculate manufacturing times and send this information to the simulation. The use of a parametric simulation model allows one to specify a more accurate end date, use of the material, equipment utilization factor and many more. The results from the simulation are returned to the scheduling where another intelligence algorithm decides to change a sorting method or not. If it is changed, a different scheduling of orders is sent to a simulation. When all the possible sorting methods have been analysed, the best method of scheduling is approved, added and sent to production (9, 10, 11, 12 and 14). Orders that are in production are frozen and do not participate in further scheduling. Module 11 searches for the required material.

(11) 93. Studies & Proceedings of Polish Association for Knowledge Management No. 60, 2012. and decides which palette will be taken. Modules 9–12 generate machine codes and send them straight to the PAC controllers. After quality control, module 12 sends important data to the report module (8). Automatically-generated reports are sent to the client and to the service module (5). If there are any machine failures or cutting accuracy is poor, module 5 sends information to module 1 to call service. At every stage of order processing information about the state of progress is updated on the database. 8. Conclusion The described system of e-Production is very complicated; despite this fact it is the simplest type of production. There are many decisions that a human can make automatically. If one wants to build a fully operational e-Production system, there is lot of programing work to do. Computer modelling is a fast and much simpler tool helping in design processes, connection, information flow and more. E-Production is a very interesting subject offering many possibilities. After finished the programming of all the modules, there will be time to compare the results of the work in a model and real machines. At present, most of the described modules are working but there is still a lot of work to do. The effects and analyses of working modules, algorithms used will be described in another article.. Bibliography [1] [2]. [3]. [4] [5]. [6] [7] [8] [9] [10]. Cheng, K. E-Manufacturing: Fundamentals and Applications, WIT Press, 2005. Jardzioch, A. and Honczarenko, J. (2004). The Application of eM-Plant Software for Constructing Virtual Manufacturing System, I International Conference “Virtual Design and Automation”. Poznan 3–4 June. Jardzioch, A. and Skobiej, B. Petri net implementation in queue algorithms analysis for flexible manufacturing systems, Foundations of Computing and Decision Sciences, 2011, Vol. 36, No. 3–4, pp. 207—217. Mrozek, Z. (2003): Modelowanie fizyczne, Pomiary Automatyka Robotyka, 4/2003. Saniuk S.: Planowanie przepływu produkcji w warunkach ograniczeĔ logistycznych, systemy wspomagania podejmowania decyzji w małych i Ğrednich przedsiĊbiorstwach. Oficyna Wydaw. Uniwersytetu Zielonogórskiego, pp. 129–162. Zielona Góra 2006. $wider, J., Baier, A., Ociepka, P. and Herbu

(12) , K. (2005). Zastosowanie metod obiektowych w procesie projektowo–konstrukcyjno-wytwórczym. In ynieria Maszyn. Teluk, T. E-biznes. Nowa gospodarka, Helion, 2002. Boxiong, L% &'*% (*% )'*% % )'% +,% puter Integrated Manufacturing System, 2004, 10 (3):pp. 241–251. Ke, H. and Liu, B. “Project scheduling problem with mixed uncertainty of randomness and fuzziness, ” European Journal of Operational Research, vol. 183, no. 1, pp. 135–147, 2007. Priore, P., Fuente, D. and Puente, J. “A comparison of machine learning algorithms for dynamic scheduling of flexible manufacturing systems,” Engineering Application of Artificial Intelligence, vol. 19, pp. 247–255, 2006..

(13) 94. Jardzioch Andrzej, Jaskowski JĊdrzej Information flow in model of e-Production systems. Internet sources: [1] http://www.plcopen.org/ 06.2012 [2] http://www.opcfoundation.org/ 06.2012. PRZEPŁYW INFORMACJI W MODELU SYSTEMU E-PRODUKCJI Streszczenie Konkurowanie w obecnych czasach nie jest moĪliwe bez umiejĊtnoĞci radzenia sobie z procesami globalizacji, szerokiego zastosowania informatyki i uzyskania wysokiej elastycznoĞci. Niedoceniany jeszcze 10 lat temu Internet, staje siĊ coraz czĊĞciej jedyną szansą dotarcia do potencjalnych klientów i producentów. Gospodarka elektroniczna pod koniec 2007 roku obejmowała swoim zasiĊgiem blisko 2 mld ludzi na całym Ğwiecie. Szeroko rozumiany e-biznes wywiera coraz wiĊkszy wpływ na strategie konkurowania przedsiĊbiorstw. Zastosowanie Internetu obejmuje coraz wiĊcej procesów gospodarczych prowadząc do powstania e-SCM (wspomaganego internetowo zarządzania łaĔcuchem dostaw) [6]. Małe i Ğrednie przedsiĊbiorstwa realizując krótkie i nieregularne zamówienia spotykając siĊ czĊsto z koniecznoĞcią realizacji zaawansowanych technologicznie przedmiotów. PrzedsiĊbiorstwa te nie mogą sobie pozwoliü na zakup drogich maszyn technologicznych posiadają jednak dostĊp do zleceĔ na realizacjĊ produktów zaawansowanych technologicznie. Rozwiązaniem w takiej sytuacji moĪe byü udostĊpnienie mocy produkcyjnych w sieci internetowej przez specjalistyczne zakłady produkcyjne w formie e-Produkcji [1,4] Jako e-ProdukcjĊ rozumie siĊ realizowanie produkcji zamawianej i programowanej poprzez sieü internetową a realizowanej na zrobotyzowanych, bezobsługowych maszynach technologicznych. Usługa e-Produkcji moĪe byü Ğwiadczona bez wzglĊdu na odległoĞü dzieląca klienta i producenta. UmoĪliwia ona dostĊp małym i Ğrednim firmom do nowoczesnych maszyn technologicznych. Z drugiej strony zakłady przemysłowe posiadające drogie specjalizowane maszyny mogą w ten sposób zwiĊkszyü liczbĊ zleceĔ oraz zwiĊkszyü wykorzystanie posiadanych maszyn. Symulacja jest obecnie jednym z najwaĪniejszych narzĊdzi wspomagających zarządzanie produkcją [5]. Presja rynku zmusza przedsiĊbiorców to rozwiązywania problemów w coraz krótszym czasie. Modelowanie systemów wytwarzania pozwala na zrozumienie problemu i opracowanie odpowiednich rozwiązaĔ jeszcze przed rzeczywistym wdroĪeniem. Modele mogą byü rzeczywiste jak i wirtualne. W wiĊkszoĞci przypadków opracowuje siĊ wiele modeli, z których kaĪdy przedstawia inne podejĞcie do rozwaĪanego problemu [3]. Wyniki symulacji komputerowej oferują nieocenioną pomoc w dynamicznie zmieniających siĊ procesach produkcyjnych [2]. Słowa kluczowe: e-Produkcja, przepływ informacji, model, symulacja.

(14) 95. Studies & Proceedings of Polish Association for Knowledge Management No. 60, 2012. Referat został podzielony na 7 cz

(15) ci. Pierwszy rozdział przedstawia przegl d literatury ze szczególnym uwzgldnieniem problematyki modelowania procesów przepływu informacji w systemach produkcyjnych. Rozdział drugi przedstawia przepływ informacji w konwencjonalnym systemie wytwarzania. W rozdziale trzecim przedstawiono now koncepcj udostpniania mocy produkcyjnej w formie e-Produkcji. Opisano przepływ informacji w systemie produkcyjnym realizuj cym proces wycinania wodnego z wykorzystaniem maszyny typu WaterJet. W rozdziale czwartym opisano zaproponowany algorytm zarz dzania zleceniami w rozwa anym systemie. Przedstawiono algorytm szeregowania zleceniami produkcyjnymi oraz problem ł czenia zlece produkcyjnych. Zdefiniowanie problemu ł czenia zlece produkcyjnych jest jednym z nowatorskich osi gni prezentowanym w pracy. W rozdziale pi tym uwaga autorów została skupiona na technicznych wymaganiach, jakie musz spełni poszczególne cz

(16) ci systemu e-Produkcji. Opisano poszczególne elementy magazynu blach, robota przemysłowego oraz wycinarki wodnej oraz struktur sieci Ethernet. Rozdział szósty przedstawia koncepcj podziału internetowego systemu udostpniania mocy produkcyjnych na moduły funkcjonalne. Wyodrbniono moduł grupowania zlece produkcyjnych w celu wycinania z jednej blachy, moduł sterowania robotem przemysłowym, moduł sterowania magazynem blach, moduł sterowania wycinark oraz moduł sterowania jako

(17) ci . W rozdziale 7 przedstawiono przepływ informacji midzy zdefiniowanymi modułami.. Andrzej Jardzioch Jdrzej Jaskowski Department of Mechanical Engineering and Mechatronics West Pomeranian Technical University of Szczecin al. Piastów 19, 72-300 Szczecin, Poland e-mail: andrzej.jardzioch@zut.edu.pl.

(18)