研究発表

We construct a make-or-buy decision-making model for a serial manufacturing system considering internal making cost and external purchasing cost. Internal making cost consists of fixed cost and variable cost, while external purchasing cost is exhaustively determined by outside supplier. Since decision-making in previous stage affects decision-making in successive stage, the model becomes quite complicated. In this paper, we introduce a binary switching variable to each production process so that to control material flow in the manufacturing system, consequently have a solution to the make-or-buy decision making observing the value of the switching variables. We prove some characteristics of the model associated with the switching variable, and develop an easy algorithm to find optimal solution.

We often use uniform distribution to describe diversity of agent values. And this description often used in agent simulation which mimics real society on computer what which we call an artificial society. In this paper we show that, an agent simulation under uniform distribution may cause wide divergence of final convergent consensus points, though we give a fixed initial macro consensus value to an artificial society facing an alternative decision. Because intuitive observation provides a same convergent value of final consensus for a given initial value of macro consensus, we call this uncertainty or divergence of the final consensus the pitfall of agent simulation. Through numerous simulations, we found that the divergent final consensus have some order %and follows zeta distribution, and the mechanism of the uncertainty were unveiled in this paper.

より良い製品企画からスムーズな生産移行に至るまでの過程において，顧客の声(VOC:Voice Of Customer)の反映，技術開発などによるロバスト性の確保，技術アイデアを再利用した企画，そして企画から販売・廃棄にいたる製品ライフサイクルの全フェーズに関連する部門が、企画や開発設計などの段階に参加・協働するCEの採用など，これらの原則を統合した新製品開発は生産者側にとって必要不可欠である．そこで本研究では，新製品の設計変数を，VOCとロバスト性という2つの視点からバランスのとれたパラメータ設計が可能になるように，多目的計画法を用いてQFDとタグチメソッドを統合し，それをさらに生産段階まで拡張を行う．

需要予測は難しい．その理由はいろいろあるが，本質的には激しい競争を通じて人工的に形成された複雑で不確実は市場が原因である．ものが足りなかった昔，衣食住行の商品予測は比較的に単純で，例えば1つの家庭において1年のおコメの消費量は正確に予測することができた．従って，全国のお米の消費量の予測も同程度の精度で予測することができた．