• Moving from Dashboards to Decisions: Using Modeling to Improve Your Metrics (2026-US-30MP-2918) In manufacturing, more operational data is being collected than ever before. Metrics are being calculated for availability, performance, quality, etc., and are broken down by days, product line, and shift. All of this is widely available in dashboards, often throughout the manufacturing floor. Production managers are able to slice the data so they can see exactly how and why production performed go...
    Skill level: intermediate
  • What's New in Warnings Triage in JMP Live 19.5 and Other Tricks (2026-US-PO-2922) It can be costly and stressful to learn about out-of-control processes late or to react to them with incomplete information. If you are one of the tens of thousands of JMP users working with control charts, you don't want to miss this talk. It gives you an updated look at a much-requested JMP Live 19 feature (now improved in JMP Live 19.5)  that can help you find and resolve issues m...
    Skill level: intermediate
  • Using JMP Profiler and Simulation to Characterize Installed Process Valves (2026-US-PO-2935) A challenge with controls – specifically, with advanced control systems – is the installed characterizations of control valves. Often times the actual installed characteristics are different from what the published characteristics state, or, frankly, the information is no longer available. Additionally, a common practice is to manipulate the valve from 0 to 100% while watching the flow, but this is...
    Skill level: beginner
  • Virtual Component Pairing for High-Precision Optical Modules via MVR Model (2026-US-PO-2915) In high-precision optics manufacturing, dual-component module assembly faces significant yield challenges due to the complex interplay between component tolerances and final performance. Current inefficiencies stem from poor pairing and uncertain specification limits, necessitating a resource-intensive "mix-and-match" bottleneck that results in substantial labor and material losses.This paper prese...
    Skill level: intermediate
  • A Discrete Event Simulation Add-in for JMP (2026-US-PO-2886) This paper presents a Discrete Event Simulation (DES) add‑in for JMP that enables users to model, analyze, and optimize complex process flows through an intuitive graphical interface. The add‑in provides a fully integrated GUI that allows users to construct simulations using configurable entity sources, queues, and processes. Entity sources support variable release timings, enabling realistic model...
    Skill level: beginner
  • Can We Talk…About Sample Size? (2026-US-30MP-2930) As soon as we start to learn about statistical tools, such as those enabled with JMP, the concept of sampling and sample size becomes important. Regulated industries, such as medical devices, require a justification of sample size determination when making design or process changes, as well as for verification/validation of performance. There is a nearly mystical relationship between sample size an...
    Skill level: beginner
  • Midnight at Sea: Saving a $1M/Day Operation with JMP and MCS (2026-US-PO-2909) Executing a DOE 100 miles offshore on a moving vessel is rarely "textbook." When unverified epoxy coating threatened the integrity of a critical 4 million pound bolt connection, we faced a midnight decision: halt million-dollar-a-day operations or prove the system was safe. Everything that could go wrong did. Initial testing suggested a special-cause wrench bias, only to discover a data-entry swap ...
    Skill level: beginner
  • Ensuring Measurement Agreement with JMP for Reliable Veterinary Diagnostics (2026-US-PO-2936) IDEXX Laboratories, Inc. develops and delivers diagnostic solutions for companion animals, livestock, poultry, water testing, and dairy markets. Ensuring high‑quality, reliable diagnostic results requires rigorous evaluation of instrument accuracy and precision. This poster presents a case study on developing a JMP add‑in to streamline measurement agreement analyses and support timely decision...
    Skill level: beginner
  • Stop Missing Out: Reliability Tools Aren't Just for Reliability Engineers (2026-US-PO-2905) Many of us have spent too much of our lives thinking that the reliability tools in JMP are just for catastrophic failures, product testing labs, or other “not my responsibility” situations. In fact, we likely already have the exact types of data that reliability methods are designed to manage. We just aren’t using these methods because we don’t recognize their applicability. This presentation serve...
    Skill level: intermediate
  • When the Question is 'Is It Comparable?', JMP Has the Answer (2026-US-PO-2964) Many modern manufacturing challenges are less a question of “Is it significant?” and more a question of “Is it comparable?”. This unique perspective, particularly in regulated environments, demands the flexibility of JMP’s recent statistical equivalency capability upgrades and JSL to answer always distinct, comparability questions. JMP can answer such customer questions as: How does equivalence com...
    Skill level: intermediate
  • Let it Be (Done Already): Saving Time with Sequential Sampling (2026-US-30MP-2897) Sequential sampling is like a relationship. After a while, we can either accept it, reject it – or keep trying. Compared to its stodgy cousin, fixed size sampling, we are nimbly making a decision every step of the way. This method has a very big advantage over the fixed size approach: it often requires far fewer parts, yet provides the same statistical power. Fewer parts means it saves time, m...
    Skill level: intermediate
  • Application of Several JMP Tools for Process Improvement: A Purification Case Study (2026-EU-30MP-2782) This presentation demonstrates how JMP tools support process optimization and online NIR implementation for reliable product quality monitoring. It includes a case study in which SPC and capability analysis are applied to assess product purity, while process control ranges are defined using DOE, Genreg/SVEM modeling, and the Design Space Profiler. For NIR-based purity modeling, PCA and FD...
  • Assessing Cell Counter Comparability Using JMP’s Measurement System Analysis Platform (2026-EU-30MP-2835) Accurate measurement of viable cell density (VCD) and viability is essential for consistent performance in cell culture processes. Automated cell counters are widely used, but ensuring their comparability is critical for data integrity and reliable decision making. Instrument and operator variability can introduce measurement error, affecting process control and product quality. Without a statistic...
  • Precision by Design: Applying DOE and MSA to Engineer Robust Measurement Systems (2026-EU-30MP-2631) This talk focuses on enhancing precision in metrology experiments through structured methodologies and robust validation of measurement systems. It introduces KLA’s role in the electronics ecosystem, showcasing its core competencies in illumination sources, optics, sensors, mechanics, physical sciences, and image and data processing. A central theme is the strategic use of design of experiments (DO...
  • Optimizing By-product Dosage in Oilseeds Processing Using JMP Pro and the DMAIC Methodology (2026-EU-PO-2841) At one of ADM’s EMEA oilseeds plants, the operations team faced a familiar but complex question: how much by-product is just right? Adding by-product increases the commercial value of the product, but only up to the point where process constraints start to push back. Finding that balance required both a structured approach and powerful analytics. Using JMP Pro within the DMAIC (Define, Measure, Ana...
    Skill level: beginner
  • Detecting Sudden Process Time Variations in a Semicon Fab using Non-standard Control Charts (2026-EU-PO-2840) This poster is about tracking how long wafers – the thin slices of material used to build chips – spend inside a piece of equipment during a specific manufacturing step. Essentially, we're monitoring the equipment's process time. Sometimes, due to maintenance or other production events, these times can suddenly change or "drift." Our main goal was to create a statistical method that could...
    Skill level: beginner
  • From Fragmented Data to Real-Time Insights: A CPV Application for Advancing Pharma Quality Using JMP (2026-EU-PO-2794) In the pharmaceutical industry, there is a requirement to understand how a product performs throughout its lifecycle. This paper presents the Bausch Health CPV application – a multidisciplinary analytics solution developed in conjunction with KPA using JMP Scripting Language – to automate data integration and advanced statistical analysis for meaningful product understanding. Th...
  • Building Surrogate Models in JMP: Combining Statistical and Physical Modelling Techniques (2026-EU-30MP-2776) This presentation highlights the application of statistical modelling to perform sensitivity analysis and optimisation of complex physical models more efficiently and effectively.   Physical models can often be complex, as it is the reality that they are representing, which requires significant resources for performing sensitivity analysis and makes their optimisation very chall...
    Skill level: beginner
  • Building an Analytics Culture in New Product Development (2026-EU-30MP-2790) A systematic, data-driven approach to new product development and manufacturing leads to products of higher quality, at lower cost. This paper shares the approach of building an analytics culture at W. L. Gore. Using systematic experimentation with data-driven decisions that are based on statistical methodology with JMP was vital to implementing this approach. A key element...
    Skill level: beginner
  • Solve Costly Out-of-Control Processes in JMP Live (2025-JA-25MP-2482) プロセスが管理不能になっていることを遅れて知ったり、不完全な情報で対応したりすることは、コストがかかり、ストレスの多いことになりかねません。もしあなたが管理図を扱っている数万人のJMPユーザーの一人であるなら、この講演を見逃すべきではありません。これは、JMP Live 19に搭載される、多くの要望が寄せられていた新機能をいち早くご紹介するものです。この機能は、問題をより迅速に、より正確に、より自信を持って発見し解決するのに役立ちます。この講演では、以下の方法を学ぶことができます。・同僚とのコミュニケーションを、管理図だけでなく、個々の警告について行う方法: ・「対応中です。」(ステータス) ・「担当者はこの人です。」(担当割り当て) ・「現状についてこのように考えています。」(メモ)・警告やそれらに対して下された決定に関する詳細情報を確認し、ダウンロードする方法。・取り組みを集中させる方法...
  • 超設計のしくみと活用法 (2025-JA-PO-2728) 設計とはもの・サービス・システムを生み出す(作る,創る)ための条件決定(因子と水準の決定)を行うことである.これを科学的に行うためにはKKD(経験と勘と度胸)だけに頼るのではなく数理に基づいた客観的なアプローチを活用する必要がある.本研究は最初に設計というものについての「しくみ」(どういう数理構造の方法なのか)と「活用法」(創造的・戦略的な使い方はどうすればよいのか)の整理を行う.そのうえで新たな設計法である「超設計」のしくみと使用法を紹介する.この新しい設計法は設計の適用範囲を大きく広げるとともに高度な設計が可能であることを明らかにする.発表の際に「超設計」という新しい設計法について分かり易い3つの例を取り上げてこの設計法の「概念(What)」と「理論(Why)」と「技法(How)」を多角的な視点から説明する.その際に①「コイン射撃」(厚紙と輪ゴムで作成したカタパルトでコインを飛ばすこと)...
  • 市場不良の返品数の予測 JMPの信頼性予測で生産数と返品数の時系列データから将来の返品数を予測する時は適合故障モデルの選択がポイントとなる。故障モデルは製品全体と型式やバージョンで異なることがあるし、経過と共に変化することがある。産業機械、計量機器、電子機器、自動車部品などの信頼性予測の指導経験では、部分故障が圧倒的に多い。摩耗故障モードで全体故障の場合は累積故障率と返品数が時間と共に増加し続けるが、部分故障では累積故障率が時間と共に頭打ちになり故障発生数が0に収束する。累積故障数も控えめな数字になる。つまり部分故障か否かは重要なポイントとなる。故障モデル判定の拠り所はモデルの比較のテーブルの統計量や尤度比検定であるが、予測時期が早いと部分故障か全体故障か判定に迷うことがある。部分故障が発生する原因についても考察する。信頼性予測で準備するデータは欠測値があっても、故障数が少なくても良い。出荷時期と稼働開始時期にズレ...
  • 「電池の個性」を解き明かす!”取りっぱなしデータ”の解析で「品質保証」から「性能・工程改善」へ (2025-JA-PO-2709) エナジーウィズ(株)は、自動車・産業用蓄電池及び電源機器の製造・販売を通じて社会を支える企業である。当社では長年に渡り、各種製品について定期的な抜き取り検査を実施し、性能が基準値を満たしているか否か確認して品質を担保してきた。この検査データは社内システムに記録されるが、可否判定上は記録データを使用する必要がないため、捨て同然の”取りっぱなし”状態で保管されていた。そこで、膨大な検査データをビッグデータと捉え、JMPを活用したデータ成形や可視化、機械学習を実施すると、今まで技術者が知り得なかった様々な知見を獲得することができた。特に、「電池の個性」を解き明かすために必要な”性能ばらつき”の把握ができた。具体的には、電池の性能ばらつきを単なる標準偏差で評価するのではなく、JMPがビッグデータを扱えるメリットを活かして、同じ製造ロット内と異なる製造ロット間のばらつきに分解、評価することで、各製品の...
    Skill level: beginner
  • 開会のご挨拶/基調講演:イノベーションの拡大:エンジニアリング・ワークフローへのデータサイエンス統合 10:00~10:15:開会のご挨拶10:15~11:15:基調講演今日のエンジニアリングにおける課題は、もはや局所的な解決策だけでは不十分です。データサイエンスの手法をデータ分析のワークフローに組み込むための、拡張性が高く柔軟なツールが求められています。JMPの製品群は、統計解析、プロセス最適化、データ視覚化のための強力なプラットフォームを提供し、エンジニアが日々の問題解決を超えて活躍できる環境を創造します。このセッションでは、複雑で大規模な問題への取り組みに焦点を当て、JMPがどのようにエンジニアリング・データサイエンスを支援するかを深掘りします。あわせて、データアクセス、プロセススクリーニング、環境モニタリング、グループ別分析、モデル・応答スクリーニング、そしてJMP Liveとの統合といったツールに焦点を当て、JMPが多様なニーズにどのように対応するかを解説します。具体的な事例やデモ...
    Skill level: beginner
  • Short Runs, Big Data, No Problem: A Control Chart Remix (2025-US-30MP-2585) As manufacturing processes grow more complex, so does the challenge of effectively monitoring the countless input and output parameters that drive quality and yield. Traditional control charts often fall short when faced with high-dimensional data or small batch sizes run across shared equipment. This session explores an innovative solution: a short run model driven multivariate control chart that ...