Chemical Product Pyramid CHEMICAL PRODUCT ENGINEERING ASEP MUHAMAD SAMSUDIN.

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Presentation transcript:

Chemical Product Pyramid CHEMICAL PRODUCT ENGINEERING ASEP MUHAMAD SAMSUDIN

Introduction  Customers generally do not judge their value based on technical specifications, but rather according to functionality and performance attributes, such as smell and handling properties.  These attributes, used to express and characterize the quality of the product from the customer perspective, are usually referred to as quality factors.  Because quality factors are often inherently qualitative and subjective, quantitative parameters have to be developed to model them. These are called performance indices.

Performance Indices  Performance indices (and therefore quality factors) are determined by three main factors: 1. The composition and physicochemical properties of the materials forming the product. 2. Product structure, which is dependent on the manufacturing process. 3. Product usage conditions.  The dependence between performance indices and product composition, product ingredients’ properties and product structure (when applicable) has been mathematically systematized through the concept of property function,

 An interesting example to illustrate the concepts of quality factor, performance index and property function comes from perfumery  The performance of a fragrance, which relates to its olfactory perception, has been empirically described in terms of four quality factors : 1. Impact (measures the efficacy of the fragrance during the first instants after application); 2. Diffusion (refers to the distance over which the fragrance is perceived soon after application); 3. Tenacity (expresses the long-term efficacy of the fragrance) and 4. Volume (relates to the distance over which the fragrance is noticed some time after application).  The odor value can be used to quantitatively express the performance of the fragrance ( performance index ).  Recently, Mata et al. applied thermodynamics and transfer phenomena fundamentals to develop a model ( property function ) relating the odor value of a fragrance to its composition, volatility and threshold concentration of its components, and activity coefficients expressing the interaction between the fragrant components and the solvent. Source : google.com

 In the case of chemical products, in contrast to commodities, product structure often has a preponderant influence over functionality and end-use properties.  The desired product structure requires selection of the proper product ingredients, but is often determined largely by the manufacturing process.  Consider chocolate — the crystal form of the cocoa butter, which is determined by the tempering process during manufacture, is key to product quality since it determines chocolate melting point and, therefore, the mouth feel.  The relationship between process conditions and structural attributes of a chemical product can be quantified by a process function, the definition being analogous to that of a property function.

 In addition to product composition, product ingredients’ properties and product structure, the circumstances under which a chemical product is used also affect its perceived quality.  Parameters describing the way the customer uses the product (such as the magnitude of shear forces as body lotion is applied and quantity of perfume employed) and environmental conditions under which product usage takes place (for example, temperature, humidity level and substrate over which a paint is applied) cannot be directly controlled.  Under the Taguchi notation they correspond to noise factors affecting product performance and, therefore, demanding robustness from the product.  Adopting the same reasoning as for the definition of property and process functions, usage functions relating performance indices to customer interaction parameters and usage environmental conditions can also be established.

 The idea of a Chemical Product Pyramid is introduced to systematize the relationships between the product recipe, materials’ physico-chemical properties, process variables, product structural attributes, usage variables and product quality factors  The base of the three-sided pyramid is defined by the materials space, process space and usage space, which determine the chemical product space occupying the top of the pyramid.  The chemical product pyramid corresponds to the technical core of chemical product engineering — in practical terms, the discipline is concerned with the development of property functions, process functions and usage functions and their application, through simulation and optimization, to the design and manufacture of chemical products with end-use properties valued by the customer.

Quality factors Performance Indices Structural Attributes Quantitative compositor Physicochemical properties Usage variables (Customer interaction parameters & environmental conditions) Operating variables Materials Usage Process Property function Usage function Process function Chemical Product Property function

Example : Ice Cream  Ice cream is valued by consumers for its flavor, its creaminess and smoothness, and its coolness; these are its quality factors.  Flavor is determined primarily by the ingredients used — a property function would relate the ingredient recipe to empirical descriptions of flavor perception.  Smoothness and creaminess are controlled as much by processing conditions as by the nature of the ingredients — the keys are the stabilization of air bubbles by fat particles, and keeping ice crystals below about 100 µm in size. A process function would describe this.  The consumers’ perceptions of both flavor and texture are strongly modulated by environmental and use factors.  In particular the storage history affects ice crystal size by Ostwald ripening. Serving temperature, ambient conditions and general ambiance also influence perceived flavor and texture. This could be described by a usage function.  The property and process functions should be controlled to ensure that the product quality factors are robust to variations in the usage function.

Quality factors: Flavor, creaminess, smoothness, coolness Performance Indices Structural Attributes ingredients Physicochemical properties Storage history, Serving temperature, ambient conditions and general ambiance stabilization of air bubbles by fat particles keeping ice crystals below about 100 µm in size Materials Usage Process Property function : the ingredient recipe Usage function Process function : to meet process condition Chemical Product : Ice cream Property function

Quality Factor Perfomance Index Key Material Physco- chemical Properties and Composition Key Product Structural Atribute Property Function Key Process Variable Process Function Key Usage Variable Usage Function Controlled release of the active ingredient Concentration of the active ingredient in the plasma (mean error of temporal profile over target nominal value) Partition coefficient of the active ingredient between the continuous phase and the dispersed phase Diffusion coefficient of the active ingredient through the continuous Phase Droplet size Mass transfer Model describing transference of the active ingredient from the ointment to the blood, comprising a series of interphase equilibria and diffusion Processes Mixing speed Mixing time Droplet break-up model balancing interfacial tension and disruptive forces Time between applications Quantity applied Skin surface of application Patient blood Volume Dynamic model able to predict The concentration of active ingredient in the plasma depending on the values assumed for specific usage Conditions Paint formulation (P. Saraiva, unpublished data, January 2006.)

Quality Factor Perfomance Index Key Material Physco- chemical Properties and Composition Key Product Structural Atribute Property Function Key Process Variable Process Function Key Usage Variable Usage Function Paint aesthetics on the wall Paint whiteness (expressed in terms of panel Evaluation against standards) Pigments concentr ation Resin concentr ation Homogen eity (expressed in terms of a dispersion statistics) Statistical models, derived from laboratory data, relating the paint whiteness to the mass fractions of pigment and Resin Mixing speed Mixing time Statistical model relating the paint homogen eity to mixing time and mixing speed Number of coats Applicati on temperat ure and humidity Substrate condition s Wall washing practices Statistical models, derived from experimental data, relating the paint whiteness to the paint application conditions and practices and wall uses. Paint formulation (P. Saraiva, unpublished data, January 2006.)