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Author:Nieminen, Ilkka
Title:Tuotantolinjan aikatauluttaminen online-optimointia käyttäen
Production line schedulíng using online-optimization
Publication type:Master's thesis
Publication year:2012
Pages:92 + [15]      Language:   fin
Department/School:Koneenrakennustekniikan laitos
Main subject:Tuotantotekniikka   (Kon-15)
Supervisor:Niemi, Esko
Instructor:Tokola, Henri
OEVS:
Electronic archive copy is available via Aalto Thesis Database.
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Location:P1 Ark Aalto     | Archive
Keywords:scheduling
reschedulig
production line
optimization
online-optimization
production planning
mathematical programming
flow shop
no-wait
aikatauluttaminen
uudelleenaikatauluttaminen
tuotantolinja
optimointi
online-optimointi
tuotannonohjaus
matemaattinen ohjelmointi
CPLEX
CONWIP
Abstract (eng):Productivity can be improved by the means of production planning using schedule optimization. The real world applications for online-optimization, in which schedule is optimized e.g. when a new job arrives, have been hindered by the lack of information. By using current IT-systems, it is possible to gather necessary information from production processes to make online-optimization possible. In this thesis, several production line environments were modelled and studied. The results from online-optimization were compared to the corresponding offline results, in which all the jobs are known from the start.

The selected production environments were flow shop, permutation flow shop, no-wait flow shop, CONWIP-variants of these three, and open shop. First, mathematical models were written for these environments in OPL-language. Object function for the models was tardiness minimization. Then, the models were solved by using software caned IBM ILOG CPLEX Optimization Studio. Every model was solved 50 times using different data with same parameters to emulate the stochastic nature of real production environment and give the results statistical meaning. This was done to every selected parameter set. The parameters were arrival rate of jobs, CV for processing times and due-date tightness. The data was randomized in Microsoft Excel. Last, the requisite graphs were constructed from the results and analysed.

The results from online-situation pointed out that the most flexible environments, like flow shop and open shop, performed best in terms of tardiness when looking at absolute numbers. Flow shop also performed best by relative-to offline numbers in online situation, whereas open shop had worst results due to its very low offline tardiness. (CONWIP) no-wait flow shop had low relative numbers and had best results alongside flow shop. Permutation and CONWIP permutation flow shop had very poor relative results, mainly due to their inability to handle situations, where several short jobs arrived after a long one. This may, however, have been affected by the fact that jobs were started as soon as possible.
Abstract (fin):Tuotannon tehokuutta on mahdollista parantaa tuotannonohjauksellisin keinoin aikataulua optimoimalla. Online-optimoinnin, jossa aikataulua optimoidaan uudestaan esimerkiksi uusien tilausten saapuessa, soveltamista oikeaan tuotantoon on rajoittanut varsinkin tarvittavan informaation saaminen tuotantoprosesseista. Nykyaikaisilla IT -järjestelmillä olisi mahdollista kerätä tarvittavaa tietoa prosesseista online-optimointia varten. Tässä diplomityössä tutkitaan eri tuotantolinjatyyppien käyttäytymistä online-ympäristössä ja verrataan sitä offline-tilanteeseen, jossa kaikki tilaukset tiedetään etukäteen.

Tutkittaviksi tuotantolinjoiksi valittiin flow shop, permutaatio flow shop, no-wait flow shop, näiden kolmen tapauksen CONWIP-variaatiot, ja open shop. Valituista tuotantolinjatyypeistä kirjoitettiin matemaattiset optimointimallit OPL-kielellä ja ne ratkaistiin käyttämällä IBM ILOG CPLEX Optimization Studio ohjelmaa. Optimointikriteerinä käytettiin kokonaismyöhästymän minimointia. Jokaiselle mallille tehtiin useita toistoja samoilla parametreilla, jotta stokastisilla malleilla saatuihin tuloksiin saataisiin tilastollista varmuutta. Tämä tehtiin kaikille valituille parametrikombinaatioille. Parametreina oli töiden saapumisväli, prosessointiaikojen vaihtelu ja aikataulun tiukkuus. Koedata arvottiin käyttäen Microsoft Excel -taulukkolaskentaohjelmaa.

Saaduista tuloksista voitiin päätellä, että joustavimmat linjatyypit, kuten flow shop ja open shop, saivat alhaisimmat absoluuttiset kokonaismyöhästymän arvot online-tilanteessa. Tarkasteltaessa kokonaismyöhästymän suhteellista kasvua offline- ja online-tilanteiden välillä, olivat flow shop ja (CONWIP) no-wait flow shop testin parhaat suoriutujat, kun taas open shop hävisi eniten alhaisen offline-myöhästymän takia. Huonoja tuloksia saivat myös permutaatio ja CONWIP permutaatio flow shop. Tämä johtui pääosin siitä, että mallit eivät selviytyneet tilanteista, joissa pitkän työn jälkeen saapui useampi lyhyt työ. Permutaatiomallien tuloksiin saattoi kuitenkin vaikuttaa se, että työt aloitettiin mahdollisimman aikaisin.
ED:2013-03-18
INSSI record number: 45965
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