Product lifecycle management with knowledge management as a strategic approach for innovative enterprise environment

Process planning knowledge (PPK) is one of the most important knowledge in production manufacturing enterprise. This paper analyzes the PPK and the concept of process planning information model (PPIM) implemented in production enterprise. In second part of the paper, there is done the basic information about PLM concept as a business strategy for product development where are included PPK and PPIM approaches, strategy which offer possibilities for innovation. Product Lifecycle Management (PLM) is the process of managing the whole life cycle of a product starting from generating an idea, concept description, business analyzes, product design, solution architecture and technical implementation, to the successful entrance to the market, service, maintenance and innovative product improvement

Inteligentno projektiranje procesa za konkurentno inženjerstvo

Process planning is one of the key activities for product design and manufacturing. The impact of process plans on all phases of product design and manufacture requires high level of interaction of different activities and close integration of them into a coherent system. This paper presents a process model of product development with manufacturing approach based on intelligent process planning techniques with focus on optimal selection of manufacturing parameters. Some derivations of the computing model for analysis of machining conditions by optimal determination of the cutting parameters in multi-pass NC machining activities are made with implementation of new evolutionary computation techniques. Genetic Algorithm (GA) based optimization method and deterministic optimization method (DO) are developed and then implementations into real manufacturing process planning for new product developed are analyzed. The results showed that both the developed optimization methods (GA and DO), especially GA, are effective methods for solving multi-objective optimization problems during the manufacturing process planning and cutting parameters selection.Planiranje procesa je jedna od ključnih aktivnosti u konstrukiciji i proizvodnji proizvoda. Utjecaj procesnih planova na sve faze konstrukcije i proizvodnje proizvoda zahtjeva visoku razinu interakcije različitih aktivnosti i jaku integraciju u jedinstven sustav. Ovaj rad predstavlja model razvoja proizvoda koristeći proizvodni pristup baziran na tehnikama inteligentnog procesa planiranja. Žarište je usredotočeno na optimalan odabir proizvodnih parametara. Neke varijante računalnog modela u analizi uvjeta obrade određenjenjem optimalnih obradnih značajki u višestrukoj NC obradi, razvijene su, a potom i analizirane primjene novih evolucijskih računalnih tehnika. Razvijeni su Genetički algoritam (GA) kao optimizacijska metoda te deterministička optimizacijska metoda (DO). Potom, za razvijen proizvod, su analizirane primjene u realnom proizvodnom procesu planiranja. Rezultati pokazuju da su obje optimizacijske metode (GA i DO), posebice GA, efikasne u rješavanju multi-objective optimizacijskim problemima tijekom planiranja procesa i odabiru značajki obradbe

Sustainable business solutions through lean product lifecycle management

In today\u27s process manufacturing environment, innovation is viewed as critical to sustainable growth and business profitability. While open innovation is regarded as the answer, the companies can effectively measure the return on R&D investment, have acceptable product success rates, achieve acceptable promotional effectiveness, or have visibility into their compliance risks or operational readiness for new product launches. While open innovation is an actual topic, capitalizing on the opportunity requires holistic strategy, not just increased collaboration. Companies must have repeatable, compliant and responsive business processes, global information infrastructure that provides a single source of the truth, alignment across departments and solutions that evolve without coding. With holistic strategy and supporting infrastructure, companies can consistently minimize the time to scale, improve product success rates and promotional effectiveness, and enjoy sustainable and profitable growth. With open innovation providing unlimited opportunities, the company should start to identify the best open innovation opportunity and deliver top and bottom line of the company\u27s benefits. The companies must first focus on the needs of their customer, continually minimize time to scale, eliminate waste, drive out costs and improve. These are core concepts of a Lean strategy. This paper will describe how Lean concept with PLM business strategy can leverage Lean with integrated compliance, continual improvement and other PLM best practices to increase the return on R&D investments and provide sustainable and profitable growth for business processes mainly manufacturing processes. The purpose of this paper is to review PLM approach linked to Lean concepts in order to achieve sustainable and innovative business processes with sustainable and profitable growth

APPLICATION OF THE PERFORMANCE SELECTION INDEX METHOD FOR SOLVING MACHINING MCDM PROBLEMS

Complex nature of machining processes requires the use of different methods and techniques for process optimization. Over the past few years a number of different optimization methods have been proposed for solving continuous machining optimization problems. In manufacturing environment, engineers are also facing a number of discrete machining optimization problems. In order to help decision makers in solving this type of optimization problems a number of multi criteria decision making (MCDM) methods have been proposed. This paper introduces the use of an almost unexplored MCDM method, i.e. performance selection index (PSI) method for solving machining MCDM problems. The main motivation for using the PSI method is that it is not necessary to determine criteria weights as in other MCDM methods. Applicability and effectiveness of the PSI method have been demonstrated while solving two case studies dealing with machinability of materials and selection of the most suitable cutting fluid for the given machining application. The obtained rankings have good correlation with those derived by the past researchers using other MCDM methods which validate the usefulness of this method for solving machining MCDM problems

Lean PLM - Information technology strategy for innovative and sustainable business environment

In today’s process manufacturing environment, innovation is viewed as critical to sustainable growth and business profitability. While innovation is regarded as the answer, the companies can effectively measure the return on R&D investment, have acceptable product success rates, achieve acceptable promotional effectiveness, or have visibility into their compliance risks or operational readiness for new product launches. Companies must have repeatable, compliant and responsive business processes, global ICT information infrastructure that provides a single source of the truth, alignment across departments and solutions that evolve without coding. With holistic strategy and supporting infrastructure, companies can consistently minimize the time to scale, improve product success rates and promotional effectiveness, and enjoy sustainable and profitable growth. The companies must first focus on the needs of their customer, continually minimize time to scale, eliminate waste, drive out costs and improve. These are core concepts of a Lean strategy. This paper will describe how Lean concept with PLM business strategy can leverage Lean with integrated compliance, continua

Inteligentno projektiranje procesa za konkurentno inženjerstvo

Process planning is one of the key activities for product design and manufacturing. The impact of process plans on all phases of product design and manufacture requires high level of interaction of different activities and close integration of them into a coherent system. This paper presents a process model of product development with manufacturing approach based on intelligent process planning techniques with focus on optimal selection of manufacturing parameters. Some derivations of the computing model for analysis of machining conditions by optimal determination of the cutting parameters in multi-pass NC machining activities are made with implementation of new evolutionary computation techniques. Genetic Algorithm (GA) based optimization method and deterministic optimization method (DO) are developed and then implementations into real manufacturing process planning for new product developed are analyzed. The results showed that both the developed optimization methods (GA and DO), especially GA, are effective methods for solving multi-objective optimization problems during the manufacturing process planning and cutting parameters selection

Optimization of the characteristic parameters in milling using the PSO evolution technique

Izbira rezalnih parametrov je najpomembnejši korak pri postopku načrtovanja proizvodnje, zato izdelamo novo tehniko razvojnega računanja za optimiranje procesa odrezovanja. V prispevku je uporabljena tehnika, ki oponaša dinamiko delcev v velikih skupinah (optimizacija PSO), za učinkovito in simultano optimiranje postopkov frezanja. V omenjenih postopkih smo soočeni s problemom več ciljnih dejavnikov. Najprej uporabimo umetno nevronsko mrežo (UNM) za napovedovanje rezalnih sil, nato z algoritmom PSO pridobimo optimalno rezalno hitrost in podajanja. Cilj optimizacije je, ob upoštevanju omejitev, določiti ekstrem ciljne funkcije (napovedna površina največjih sil). Med optimizacijo delci, s svojo inteligenco, letijo po prostoru rešitev in iščejo optimalne rezalne pogoje po strategiji algoritma PSO. Rezultati pokažejo, da je integriran sistem nevronskih mrež in kolektivne inteligence učinkovita metoda pri reševanju večciljnih optimizacijskih problemov. Njena velika učinkovitost na širokem območju rezalnih parametrov potrjuje, da sistem lahko praktično uporabimo v proizvodnji. Rezultati simulacij nakazujejo, da predlagan algoritem v primerjavi z rodovnimi algoritmi (GA) in simulacijskim (SA) ohlajanjem lahko poveča natančnost rešitve in konvergenco postopka. Nova tehnika razvojnega računanja ima nekoliko prednosti ter koristi in je primerna za uporabo v kombinaciji z modeli na osnovi umetnih nevronskih vezij, pri katerih niso na voljo izrecne relacije med vhodi in izhodi. Raziskava odpre vrata na področju obdelave z odrezovanjem za nov razred optimizacijskih tehnik, ki slonijo na razvojnem računanju.The selection of machining parameters is an important step in process planningtherefore, a new evolutionary computation technique has been developed to optimize the machining process. In this paper, Particle Swarm Optimization (PSO) is used to efficiently optimize the machining parameters simultaneously in milling processes where multiple conflicting objectives are present. First, an artificial neural network (ANN) predictive model is used topredict the cutting forces during machining and then the PSO algorithm is used to obtain the optimum cutting speeds and feed rates. The goal of the optimization is to determine the objective function maximum (the predicted cutting-force surface) by considering the cutting constraints. During optimization the particles \u27fly\u27 intelligently in the solution space and search for optimal cutting conditions according to the strategies of the PSO algorithm. The results showed that an integrated system of neural networks and swarm intelligence is an effective method for solving multi-objective optimization problems. The high accuracy of the results within a wide range of machining parameters indicates that the system can be practically applied in industry. The simulation results show that compared with genetic algorithms (GAs) and simulated annealing (SA) the proposed algorithm can improve the quality of the solution while speeding up the convergence process. The new computational technique has several advantages and benefits and is suitable for use when combined with ANN-based models where no explicit relation between the inputs and the outputs is available. This research opens the door for a new class of optimization techniques that are based on evolution computation in the area of machining

Enterprise: performance and business processes

This article proposes a scenario of Product Lifecycle Management (PLM), as a innovative business strategy based on the analysis of business drivers, industry requirements, limit of current solution, and recent state-of-the-art review in the domain related to PLM. Potential industrial impact of the developed PLM technology solutions is analyzed. It is hoped that the proposed PLM technology solutions will form the frontier basis for further research, development, and application of PLM systems to quickly adapt to the dynamic changing market for industry companies to pursue the most advanced competitiveness. This article presents a process oriented framework to support effective PLM implementation with a set of lifecycle oriented business process reference models which links the necessary fundamental concepts, enterprise knowledge and software solutions to effectively deploy PLM