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Smart Manufacturing Concepts and Methods FIRST EDITION
Masoud Soroush Michael Baldea Thomas F. Edgar
Table of Contents Cover image Title page Copyright Contributors Preface Chapter 1: Smart manufacturing: It's a journey, not a destination Abstract 1: Introduction 2: The “Smart Manufacturing” north star vision 3: Strategy 4: Execution 5: Conclusion Chapter 2: Implementing smart manufacturing across an industrial organization
Abstract 1: Introduction 2: Smart Manufacturing examples at Linde 3: Summary 4: Conclusion Chapter 3: Industrie 4.0 and international perspective Abstract 1: Introduction 2: RAMI 4.0 3: Asset administration shell 4: Applications 5: Roadmap/ongoing research 6: Conclusion Chapter 4: Cyberinfrastructure for the democratization of smart manufacturing Abstract Acknowledgments 1: Introduction 2: Smart Manufacturing and democratization 3: Today's complexity of interconnectedness
4: Reducing the heavy lift of data modeling and contextualization 5: The data-centric view of Smart Manufacturing 6: The building blocks of Smart Manufacturing 7: Operational data models, SM Profiles, and the SM Innovation Platform 8: Overarching R&D considerations 9: Conclusion Chapter 5: The role of hardware and software in smart manufacturing Abstract 1: Introduction 2: Hardware 3: Software 4: Conclusion Chapter 6: Measuring, managing, and transforming data for operational insights Abstract Acknowledgments 1: Quick look backward
2: Modern data infrastructure approach to manufacturing data collection and analysis 3: Plant operations—The silo issue 4: Simplifying the integration of plant data and control hierarchy 5: Using operations data for enterprise or division-level data analytics 6: Collecting the data for intelligent analysis 7: Condition-based and predictive asset management 8: Control loop performance monitoring 9: Beyond the enterprise—Community collaboration using OSIsoft's connected services 10: Conclusion Chapter 7: The role of advanced process modeling in smart manufacturing Abstract Acknowledgments 1: Introduction 2: Model development 3: From data and model to value 4: Going on-line 5: Model reduction
6: Case study 7: Industrial needs 8: Conclusion Chapter 8: Industrial AI and predictive analytics for smart manufacturing systems Abstract 1: Introduction 2: The four enabling technologies for industry 4.0 3: Case study: Intelligent bandsaw system 4: Challenges 5: Conclusion Chapter 9: Computational framework for smart manufacturing via parametric optimization and control (PAROC) Abstract 1: Introduction 2: Smart manufacturing concepts 3: Computational framework in smart manufacturing 4: Case study: Application of PAROC framework to optimal hydrogen storage operation 5: Future opportunities 6: Conclusion
Chapter 10: A systems engineering-driven decomposition approach for large-scale industrial decision-making processes Abstract 1: Introduction 2: Optimization methods for complex integrated systems 3: Mathematical optimization: A review 4: Multidisciplinary systems design optimization approaches 5: Multicriteria optimization 6: Maximizing steel rolling throughput: Illustrative use case of manufacturing systems formal decomposition and optimization 7: Future steps toward full manufacturing systems autonomy: Advanced probabilistic and control approaches 8: Conclusion Chapter 11: Model-predictive safety: A new evolution in functional safety Abstract Acknowledgments 1: Introduction 2: Current industry-standard functional safety systems 3: Alarm management and interlocks 4: Univariate reactive vs. multivariate predictive safety indicators
5: Data-driven predictive risk assessment 6: Digital twin 7: Model-predictive safety 8: Application of model-predictive safety to a process example 9: Conclusion Chapter 12: Inferential modeling and soft sensors Abstract 1: Introduction 2: Characteristics of process data 3: Inferential control and state estimation-based approaches 4: Data-driven soft sensors 5: Points of view 6: Smart manufacturing as new enabler 7: Conclusion Chapter 13: A decision support framework for sustainable and smart manufacturing Abstract Acknowledgments 1: Introduction 2: Decision-support framework
3: Case study 4: Conclusion Chapter 14: Smart manufacturing pedagogy for the anthropocene Abstract Acknowledgments 1: Introduction 2: The landscape of smart manufacturing pedagogy 3: Smart Manufacturing as data-enabled sustainable manufacturing 4: Deploying a Smart Manufacturing pedagogy for the anthropocene 5: Conclusion Index
Copyright Elsevier Radarweg 29, PO Box 211, 1000 AE Amsterdam, Netherlands The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, United Kingdom 50 Hampshire Street, 5th Floor, Cambridge, MA 02139, United States © 2020 Elsevier Inc. All rights reserved. No part of this publication may be reproduced or transmi ed in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions. This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein).
Notices Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary. Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety
and the safety of others, including parties for whom they have a professional responsibility. To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a ma er of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein. Library of Congress Cataloging-in-Publication Data A catalog record for this book is available from the Library of Congress British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library ISBN: 978-0-12-820027-8 For information on all Elsevier publications visit our website at h ps://www.elsevier.com/books-and-journals Publisher: Susan Dennis Editorial Project Manager: Devlin Person Production Project Manager: Bharatwaj Varatharajan Cover Designer: Ma hew Limbert Typeset by SPi Global, India
Contributors Majid Moradi Aliabadi Department of Chemical Engineering and Materials Science, Wayne State University, Detroit, MI, United States Jose Anaya El Camino Community College, Hawthorne, CA, United States Jeffrey E. Arbogast American Air Liquide, Newark, DE, United States Air Liquide (China) R&D Co., Ltd., Shanghai, China Styliani Avraamidou Texas A&M Energy Institute, Texas A&M University, College Station, TX, United States Moslem Azamfar NSF Industry/University Cooperative Research Center on Intelligent Maintenance Systems (IMS), Department of Mechanical and Materials Engineering, University of Cincinnati, Cincinnati, OH, United States Osvaldo A. Bascur States
OSB Digital, LLC, The Woodlands, TX, United
B. Wayne Beque e Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, NY, United States Mark Besser Customer Success, Savigent Software, Bloomington, MN, United States Sergio Butkewitsch University of Pi sburgh, Swanson School of Engineering, Department of Industrial Engineering, Pi sburgh, PA, United States
Greg Colvin Additive Manufacturing, Honeywell Aerospace— Advanced Technology, Phoenix, AZ, United States James Davis University of California Los Angeles, CESMII, The Smart Manufacturing Innovation Institute, Los Angeles, CA, United States Richard P. Donovan Sustainable Smart Manufacturing, California Institute for Telecommunications and Information Technologies, Irvine, CA, United States John Dyck University of California Los Angeles, CESMII, The Smart Manufacturing Innovation Institute, Los Angeles, CA, United States Helvio Markman Filho Circle Process Management Systems LLC, Glen Allen, VA, United States Jesus Flores-Cerrillo Lance Fountaine
Linde PLC, Tonawanda, NY, United States
Cargill, Wayzata, MN, United States
Sambit Ghosh Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, NY, United States Iiro Harjunkoski Germany Gangshi Hu
ABB Power Grids Research, Mannheim,
Linde PLC, Tonawanda, NY, United States
Yinlun Huang Department of Chemical Engineering and Materials Science, Wayne State University, Detroit, MI, United States Prakashan Korambath University of California Los Angeles, CESMII, The Smart Manufacturing Innovation Institute, Los Angeles, CA, United States Heiko Koziolek
ABB Corporate Research, Ladenburg, Germany
Jay Lee NSF Industry/University Cooperative Research Center on Intelligent Maintenance Systems (IMS), Department of Mechanical and Materials Engineering, University of Cincinnati, Cincinnati, OH, United States Haresh Malkani University of California Los Angeles, CESMII, The Smart Manufacturing Innovation Institute, Los Angeles, CA, United States Leila Samandari Masooleh Department of Chemical and Biological Engineering, Drexel University, Philadelphia, PA, United States Lawrence Megan Jim O’Rourke
Linde PLC, Tonawanda, NY, United States
OSIsoft, LLC, Houston, TX, United States
Gerald S. Ogumerem Artie McFerrin Department of Chemical Engineering Texas A&M Energy Institute, Texas A&M University, College Station, TX, United States Ulku Oktem United States
Near-Miss Management, LLC, Philadelphia, PA,
Vibhor Pandhare NSF Industry/University Cooperative Research Center on Intelligent Maintenance Systems (IMS), Department of Mechanical and Materials Engineering, University of Cincinnati, Cincinnati, OH, United States Efstratios N. Pistikopoulos Artie McFerrin Department of Chemical Engineering Texas A&M Energy Institute, Texas A&M University, College Station, TX, United States J. Pieter Schmal ExxonMobil Research & Engineering, Annandale, NJ, United States
Dirk Schulz
ABB Corporate Research, Ladenburg, Germany
Warren D. Seider Department of Chemical and Biomolecular Engineering, University of Pennsylvania, Philadelphia, PA, United States Jaskaran Singh NSF Industry/University Cooperative Research Center on Intelligent Maintenance Systems (IMS), Department of Mechanical and Materials Engineering, University of Cincinnati, Cincinnati, OH, United States Department of Mechanical Engineering, Thapar Institute of Engineering and Technology, Patiala, Punjab, India Masoud Soroush Department of Chemical and Biological Engineering, Drexel University, Philadelphia, PA, United States Jonathan Wise University of California Los Angeles, CESMII, The Smart Manufacturing Innovation Institute, Los Angeles, CA, United States Shu Yang Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, NY, United States Michael Yost Clean Energy Smart Manufacturing Innovation Institute, Los Angeles, CA, United States
Preface Research and development efforts in the past 10 years have led to considerable advances in concepts and methods in smart manufacturing. This monograph puts these advances into perspective and shows how process industries can benefit from them. It consolidates results developed by leading academic and industrial groups in this area, along with the computational tools and methods, and presents them in a systematic way. It provides comprehensive coverage of advances in concepts and methodologies. This book is complemented by the companion book entitled “Smart Manufacturing: Industrial Applications and Case Studies,” which focuses on the state-of-the art applications of smart manufacturing concepts and methods in process industries. Chapter 1, Smart manufacturing: It's a journey, not a destination, provides an introduction to smart manufacturing and points to the broad vision that smart manufacturing really represents. It highlights the importance of aligning a company around a common overarching vision of smart manufacturing, and the critical need to establish a comprehensive strategy to manage progress and success throughout the ongoing journey. It argues that smart manufacturing is a ma er of continuous improvement, not just a pursuit of new technology. Chapter 2, Implementing smart manufacturing across an industrial organization, summarizes the factors that should be considered in implementing smart manufacturing. Smart manufacturing has the potential to unlock billions of dollars of operating profit across the industry. Recent successes of the authors related to the three pillars of smart manufacturing are described: data analytics, automation, and connectivity. Chapter 3, Industrie 4.0 and international perspective, discusses the German-driven initiative Industrie 4.0 and addresses commonalities and differences. It suggests possible synergies and
shows how Smart Manufacturing and Industrie 4.0 activities can support and complement each other. It also reviews some applications within Industrie 4.0 and summarizes the development roadmap. Chapter 4, Cyberinfrastructure for the democratization of smart manufacturing, discusses the importance of the realignment of business, leadership, market and infrastructure to “democratize” “smart” business, technology, operational and workforce data practices industry-wide. It argues that this democratization is needed to realize the full economic potential of Smart Manufacturing. Chapter 5, The role of hardware and software in smart manufacturing, highlights and explains the roles and responsibilities that hardware and software play in smart manufacturing. The chapter is a primer on legacy and present-day equipment, data that are created, and data that are used in manufacturing decision making. Chapter 6, Measuring, managing, and transforming data for operational insights, discusses the need for a data-driven strategy to enable operations, maintenance, and business personnel to quickly and easily take corrective actions when abnormal conditions occur. It presents a smart unit template approach that transforms data into information, classifies the operating modes based on the variance from the plant schedule targets, simplifies the analysis and aggregation of production and consumables, and allows for fast tracking of losses by shift. Chapter 7, The role of advanced process modeling in smart manufacturing, discusses the critical role that modeling plays in many smart manufacturing approaches. It explains how firstprinciples and data-driven models can be developed and what aspects are involved to get to a validated model, including data reconciliation, state estimation, parameter estimation, design of experiments, and model selection. It elaborates on challenges in online implementation and model reduction. It demonstrates different modeling approaches using a case study. Chapter 8, Industrial AI and predictive analytics for smart manufacturing systems, presents a comprehensive overview of the
important role of key enabling technologies of industrial artificial intelligence in the manufacturing industry in general. Their systematic adoption can aid in producing new value-creation opportunities and avoidance of problems that have not even occurred yet. Chapter 9, Computational framework for smart manufacturing via parametric optimization and control (PAROC), highlights the need for efficient computational techniques to transform manufacturing data into manufacturing intelligence. It demonstrates how computational frameworks utilize the functionalities of analytical tools to create unique solutions. A case study considers refueling of a metal hydride hydrogen storage system to describe how the PAROC framework leverages high-fidelity modeling, system identification, and parametric programming to develop a unique optimal operating strategy for the system. Chapter 10, A systems engineering-driven decomposition approach for large-scale industrial decision-making processes, presents an approach that considers industrial production structures as dynamic stochastic systems, whose behavior varies with time, affected by both controllable inputs and uncertainties from various sources. To represent this behavior mathematically, it presents a framework derived from the typically design-centric Systems Engineering methodology, adapted toward manufacturing and its digital technologies. It demonstrates this approach through a case study. Chapter 11, Model-predictive safety: A new evolution in functional safety, discusses the need for innovation in functional safety to ensure safe operation of intensified processes in smart manufacturing. It presents the concept and the main components of an innovation in functional safety, namely, model-predictive safety (MPS), which unlike conventional functional safety systems, generates alarm signals that are predictive and systematically accounts for process nonlinearities and variable interactions. It describes how in real time, MPS detects potential and imminent future process operation hazards, and prescribes optimal preventive and mitigating actions proactively. It demonstrates the concept of MPS by applying it to a polymerization reactor example.
Chapter 12, Inferential modeling and soft sensors, discusses the increasing role that soft sensors are playing in advanced (smart) manufacturing. It describes the impact of soft sensors based on historical trends, and identifies future opportunities as well as the characteristics of process data and its influence on soft sensor development. A comprehensive review of both first-principles and data-driven methods for soft sensor modeling, including state estimation, principal component analysis, partial least squares, artificial neural networks, and support vector machines, is provided. Chapter 13, A decision support framework for sustainable and smart manufacturing, introduces a decision support framework for sustainable and smart manufacturing. The framework comprises a data analytics block that is responsible for both sustainability assessment and monitoring of external factors that may affect the sustainability performance of the system in its transition process. It uses a model predictive control strategy to identify and update optimal sustainability strategic plans for achieving short-to-long term sustainability goals. It provides a structured step-by-step guide to decision makers in formulating and updating sustainability strategies. Chapter 14, Smart manufacturing pedagogy for the anthropocene, presents fundamental principles from which to build a holistic framework of a smart manufacturing pedagogy for the anthropocene. Inspired by a data-centric sustainable manufacturing vision for manufacturing, it describes how fundamental and emerging complex system ideas enable convergence of broad perspectives from the humanities and social sciences into a model to leverage the tools of data science and engineering. It introduces intriguing new perspectives from complex systems and sustainability science that link information and Newtonian mechanics in order to create a dynamic repository of case studies that can drive life-long learning and set us on a path to smartly manufacture products for healthy living on a healthy planet. This book is expected to become a reference for process engineers, managers, and consultants in process industries, postdoctoral researchers, graduate students, and other researchers in academia, national labs, and process industries. It summarizes the most recent
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Cover the jar and leave it at rest. After some days the mixture will have changed into a firm mass of monocarbonate of ammonia which is rubbed to a coarse powder, perfumed, and filled into bottles. The above quantities require: Oil of bergamot 15 grains. Oil of lavender 15 grains. Oil of nutmeg 8 grains. Oil of clove 8 grains. Oil of rose 8 grains. Oil of cinnamon 75 grains. The oils are poured into a mortar and rubbed up with about onetenth of the salt; of this perfumed salt enough is added to the several portions of the mass, and triturated until the odor is equally distributed. For cheaper smelling salts oils of geranium and cassia may be substituted for the oils of rose and cinnamon. Preston Salt (Sel Volatil).
In this perfume ammonia is continually generated; the salt is prepared by mixing chloride of ammonium or sal-ammoniac in fine powder with freshly slaked lime. Fine or cheap perfume is added, according to the grade desired. The mixture of sal-ammoniac and slaked lime continually develops small amounts of ammonia—it takes a long time until the decomposition is complete, and for this reason a bottle filled with Preston salt retains the odor of ammonia for several years. Eau de Luce.
This is the only ammoniacal perfume used in a liquid form. It is made according to the following formula: Tincture of ambergris 10½ oz. Tincture of benzoin ½ lb.
Oil of lavender Water of ammonia
150 grains. 1½ lb.
The tinctures are mixed with the ammonia by agitation and immediately filled into bottles; the liquid should have a milky appearance. At times 150 grains of white soap is added which aids in imparting to the liquid the desired milky appearance. In fine eau de Luce the odor of ambergris should predominate; this can be easily effected by increasing the amount of tincture of ambergris. B. Acid Perfumes. As there is a group of perfumes which is distinguished by their characteristic odor of ammonia and which we have therefore called ammoniacal, so there is an important series of articles containing acetic acid which are used cosmetically as so-called toilet vinegars, and in some washes. Ordinary vinegar, i.e., water containing four to six per cent of acetic acid, has, as is well known, a not unpleasant refreshing odor and a pure acid taste. Pure acetic acid, now made in large quantities and of excellent quality, is known commercially as glacial acetic acid. In commerce, it is customary to designate any acetic acid containing 85 or more per cent of the absolute acid, as glacial acetic acid. In chemical or pharmacopœial nomenclature, however, the glacial acid is meant to be as near 100% as possible. In perfumery, an 85% acid is sufficiently strong. It forms a colorless liquid with a narcotic odor and an intensely acid taste; it congeals into glassy crystals at a temperature of 8.5° C. (47° F.). The latter property is of importance as showing the purity of the acid. Concentrated acetic acid, like alcohol, dissolves aromatic substances, with which it forms perfumes which differ from those made with alcohol mainly by their peculiar refreshing after-odor which is due to the acetic acid. Acetic acid can be saturated with various odors and thus furnish fine perfumes; but for so-called toilet vinegars which are used as washes the acetic acid must be properly diluted, since the
concentrated acid has pronounced caustic properties, reddens the skin, and may even produce destructive effects on sensitive parts such as the lips. Aromatic Vinegar (Vinaigre Aromatique).
Glacial acetic acid 2 lb. Camphor 4¼ oz. Oil of lavender ¾ oz. Oil of mace 150 grains. Oil of rosemary 150 grains. Instead of the perfumes here given, finer odors may be employed for the production of superior toilet vinegars; thus we find vinaigre ambré, au musc, à la violette, au jasmin, etc., according to the perfume used. As concentrated acetic acid dissolves most aromatic substances the same as alcohol, all alcoholic perfumes may have their counterparts in acetic acid; but the aromatics should never be added in so large amount as to mask the characteristic odor of the acetic acid. A very pleasant vinegar may be produced by combining an alcoholic with an acid perfume, as in the following: Spiced Vinegar (Vinaigre aux Épices).
1. Macerate: Leaves of geranium, lavender, peppermint, rosemary, and sage, of each 1 oz. In alcohol of 80% 1 lb. 2. Macerate: Angelica root, calamus root, camphor, mace, nutmeg, cloves, of each ½ oz. In glacial acetic acid 2 lb. for two weeks, mix the liquids, and filter them into a bottle which should not be completely filled. The longer this mixture is allowed to
season in the bottle, the finer will be the aroma; for in the course of time the alcohol and acetic acid react on each other and form acetic ether, which likewise possesses a pleasant aromatic odor. Certain aromatic vinegars, like ammoniacal perfumes, are filled into smelling bottles containing the same porous substances for their absorption, namely, sponge, pumice stone, crystals of potassium sulphate, etc. FORMULAS FOR TOILET VINEGARS. Vinaigre a la Rose.
Essence of rose (triple) 10½ oz. White-wine vinegar 1 qt. This should be colored a pale rose tint with one of the dye-stuffs to be enumerated hereafter. The use of true wine vinegar is to be recommended for this and all the following toilet vinegars, as the œnanthic ether it contains has a favorable effect on the fineness of the odor. Vinaigre aux Fleurs d’Oranges.
Extract of orange flower 7 oz. White-wine vinegar 1 qt. This is usually left colorless. Vinaigre aux Violettes.
Extract of cassie 8 oz. Extract of orange flower 3½ oz. Tincture of orris root 5½ oz. Essence of rose (triple) 5½ oz. White-wine vinegar 1 qt.
Vinaigre de Quatre Voleurs.
Leaves of lavender, peppermint, rue, rosemary, and cinnamon, of each 3¼ oz. Calamus, mace, nutmeg, of each 150 grains. Camphor ¾ oz. Macerated in alcohol 7 oz. And acetic acid 4¾ lb. Preventive Vinegar (Vinaigre Hygiénique).
Benzoin 2¼ oz. Lavender ¾ oz. Cloves 150 grains. Marjoram ¾ oz. Cinnamon 150 grains. Alcohol 1 qt. White-wine vinegar 2 qts. Macerate the solids with the alcohol and vinegar. Vinaigre de Cologne.
Cologne water 1 qt. Glacial acetic acid 1¾ oz. As this vinegar is made by mixing an alcoholic perfume with acetic acid, so all other alcoholic perfumes may be employed for a like purpose; but the quantities must be determined by experiment, for the various aromatics differ in the intensity of their odor. Vinaigre étheré.
Glacial acetic acid 14 oz. Acetic ether 1½ oz.
Nitrous ether Water
¾ oz. 5 qts.
The water should be added after the ethers have been dissolved in the glacial acetic acid. Vinaigre de Lavande.
Lavender water 4 qts. Rose water 1 pint. Glacial acetic acid ½ lb. To be stained a bluish color with indigo-carmine. Orange-Flower Vinegar.
Orange-flower water 4 qts. Glacial acetic acid 7 oz. Mallard’s Toilet Vinegar.
Tincture of benzoin 1½ oz. Tincture of tolu 1½ oz. Oil of bergamot 150 grains. Oil of lemon 150 grains. Oil of neroli 30 grains. Oil of orange peel ½ oz. Oil of lavender 15 grains. Oil of rosemary 15 grains. Tincture of musk 15 grains. Concentrated acetic acid 21 oz. Alcohol 4¾ lb. Toilet Vinegar (French Formula).
Oil of bergamot 30 grains. Oil of lemon 30 grains. Oil of rose 8 drops. Oil of neroli 5 drops. Benzoin 75 grains. Vanillin 15 grains. Concentrated acetic acid ½ oz. Alcohol ½ lb. Macerate for two weeks, and filter. Vinaigre Polyanthe.
Glacial acetic acid 7 oz. Tincture of benzoin 1¾ oz. Tincture of tolu 1¾ oz. Oil of neroli 150 grains. Oil of geranium 150 grains. Water 2 qts. To be stained with tincture of krameria (rhatany).
CHAPTER XVI. DRY-PERFUMES. As a matter of course, dry perfumes are of greater antiquity than fluid; aromatic substances require merely to be dried in order to retain their fragrance permanently. The oldest civilized people known in history—Egyptians, Assyrians, Persians, Babylonians, and the Jews, as numerous passages in the Bible prove—used dried portions of plants, leaves, flowers, and resins as perfumes and incense. To this day there is kept up quite a trade in Valeriana celtica, a strong-scented Alpine plant, and in powdered amber, with the Orient, where they are used for scent bags and incense respectively. The Catholic Church retains to the present time the Jewish rite of burning incense, and in our museums will be found urns, taken from Egyptian graves, from which pleasant odors escape even now after nearly four thousand years, owing to the aromatic resins with which they are filled. It is said, too, that the delightful volatile odors of our handkerchief perfumes were first prepared by an Italian named Frangipanni conceiving the idea of treating a dry mixture of different aromatic plants with alcohol and thus imparting the odor they contained to the latter. Not all aromatics can be made into sachet powders; it is well known that the delightful odor of violets changes into a positively disagreeable smell when the flowers are dried, and the same remark applies to the blossoms of the lily of the valley, mignonette, lily, and most of our fragrant plants. On the other hand, some portions of plants, especially those in which the odorous principle is contained not only in the flower but in all parts of the plant, as in the mints, sage, and most Labiatæ, remain fragrant for a long time after drying and hence can be employed for sachets. Besides the plants named, lavender, rose leaves, the leaves of the lemon and orange tree,
Acacia farnesiana, patchouly herb, and some other plants continue fragrant after drying. Any vegetable substance to be used for sachets must be completely dried so as to prevent mould. The drying should be effected in a warm, shady place, sometimes in heated chambers; direct sunlight and excessive heat injure the strength of the odor, a portion of the aromatics becoming resinified and volatilized. If artificial heat is employed, a temperature between 40 and 45° C. (104-113° F.) is most suitable. The external form of this class of preparations varies of course with the public for which it is intended. Expensive sachets are sold in silk bags with different ornamentation; those intended for the Orient are generally put up as small silk cushions richly ornamented with gold and colors to suit Oriental taste. Cheap sachets are sold in envelopes or in round boxes. It is customary to have the ingredients ground or finely powdered, for which purpose small hand-mills will generally suffice.
CHAPTER XVII. FORMULAS FOR DRY PERFUMES (SACHETS). Ceylon Sachet Powder. Mace 23 oz. Patchouly 28 oz. Vetiver root 35 oz. Oil of orange peel 1¾ oz. Oil of peppermint 3½ oz. Cyprian Sachet Powder. Cedar wood 2 lb. Rhodium 2 lb. Santal wood 2 lb. Oil of rhodium ½ oz. The oil is mixed with the finely powdered or rasped woods and distributed in the mass by trituration. Field Flower Sachet Powder. Calamus root 1 lb. Caraway ½ lb. Lavender 1 lb. Marjoram ½ lb. Musk 30 grains. Cloves 2¾ oz. Peppermint ½ lb. Rose leaves 1 lb. Rosemary 3½ oz.